Changes in version 4.0.0 (2026-10-30)                  

    o   
	voomLmFit() transferred to limma from the edgeR package.
	Previously, voomLmFit() needed to call edgeR::glmFit() in order
	to identify exact zero fitted values, but voomLmFit() now calls
	a new limma C routine 'poisfit' for the same purpose, removing
	the dependence on edgeR.

    o   
	For the purpose of estimating sample weights, voomLmFit() calls
	arrayWeights() with 'method="reml"' if there is no loss of df
	due to exact zero fitted values and 'method="genebygene"'
	otherwise.

    o   
	The voomLmFit help page has been expanded, while the voom and
	voomWithQualityWeights help pages now have preambles that point
	users to voomLmFit.

    o   
	voomLmFit() now gives priority to 'offset' over 'offset.prior'
	or 'lib.size' and no longer forces the rows of 'offset.prior'
	to add to zero.

    o   
	New argument 'contrasts' for voomLmFit(), lmFit(), lm.series()
	and gls.series(), which converts coefficient estimates and
	standard deviations into contrast estimates and standard
	deviations. This argument provides the same functionality as
	calling 'contrasts.fit' on the output object, but with exact
	rather than approximate standard deviations.

    o   
	New argument 'nthreads' for voomLmFit(), lmFit(), lm.series(),
	gls.series(), duplicateCorrelation(), and arrayWeights() to
	enable OpenMP parallelization of genewise fits.

    o   
	C code backends for lm.series() and gls.series().

    o   
	C code backend for duplicateCorrelation().
	duplicateCorrelation() previously called statmod::mixedModel2()
	to estimate genewise correlations, but this functionality is
	now absorbed into the C code. The new code is able to evaluate
	the genewise SVDs needed by mixedModel2() more efficiently than
	was possible for the univariate R function, resulting in
	substantial speed and memory improvements.

    o   
	C code backend for .arrayWeightsPrWtsREML(), which is called by
	arrayWeights() when 'method="reml"' and prior weights are set.

    o   
	Minor changes to weightedLowess() C code to fit in with the new
	C code elsewhere.

    o   
	New function normalizeBetweenSamples(). Similar to
	normalizeBetweenArrays() but works on ELists.

    o   
	camera() and cameraPR() now support gene sets as expression
	signatures, whereby a logFC or similar expected directional
	change is provided for each gene in the gene set.

    o   
	avearrays() methods for EList and MAList objects now sum the
	weights instead of averaging them. Other matrices are still
	averaged.

    o   
	Fix filtering error in Agilent rat case study in User's Guide.

    o   
	All the Rd pages have been checked for typos and inconsistent
	formating, especially regarding the reference lists. Reference
	URLs converted to DOIs where possible and some new DOIs added.
	Old statsci.org/smyth/pubs preprint URLs updated to
	gksmyth.github.io/pubs URLs.  Author lists converted to compact
	PubMed style without unnecessary punctuation. A few instances
	of British spellings converted to American spellings.

    o   
	Expand changelog.txt entries for limma 1.0 and earlier.

    o   
	Minor code update to strsplit2().

    o   
	Add test files dupcor.R, gls-series-c.R, lmfit-contrasts.R,
	lm-series-c.R, and voomlmfit-contrasts.R.

                 Changes in version 3.68.0 (2026-04-28)                 

    o   
	New arguments 'offset' and 'offset.prior' for voom(). voom()
	now supports offsets in DGEList objects.

    o   
	New argument 'treat.lfc' for topSplice() to allow TREAT
	fold-change thresholding with diffSplice() output.

    o   
	In normalizeCyclicLoess(), default for 'adaptive.span' becomes
	'TRUE', and the 'span' is chosen using the default settings of
	chooseLoessSpan().

    o   
	The function topTableF(), which has been deprecated for many
	years, is now formally removed.

                 Changes in version 3.66.0 (2025-10-28)                 

    o   
	New argument 'upshot' for treat().

    o   
	New argument 'span' for fitFDistUnequalDF1(), squeezeVar() and
	eBayes().

    o   
	The default for 'adaptive.span' in voom() and
	voomWithQualityWeights() is now 'TRUE'. All the voom functions
	now use chooseLowessSpan() by default to choose the 'span'.

    o   
	New argument 'xlab' for plotSplice() to allow labeling in terms
	of transcripts or other splicing events instead of exons.

    o   
	The help pages for diffSplice(), topSplice() and plotSplice()
	have been updated to emphasize differential transcript usage
	instead of differential exon usage or differential splicing.
	"differential usage" concept tags have been added to the
	appropriate help pages, creating an entry in the reference
	manual index.

    o   
	makeContrasts() now uses the contrast names if 'contrasts' is a
	named vector.

    o   
	Fix typo in error message from makeContrasts() when the
	variable names are not syntactically valid.

    o   
	Bug fix to contrastAsCoef() when the 'contrast' matrix is not
	of full column rank.

    o   
	The columns of the 'covariates' matrix input to
	removeBatchEffect() are now mean-corrected.

    o   
	removeBatchEffect() now gives a message if 'design' is not
	specified.

    o   
	Bug fix for topTable() when 'confint=TRUE' and either 'p.value'
	is less than 1 or 'lfc' is greater than zero.

    o   
	Revise help page for lmFit(), removing out-of-date mention of
	default correlation.

    o   
	Minor edits to poolVar() and update of help page.

    o   
	Complete remaining dates for release versions in NEWS.Rd.

                 Changes in version 3.64.0 (2025-04-16)                 

    o   
	In topSplice(), the default for 'test' is now "F" instead of
	"simes".

    o   
	diffSplice() is now an S3 generic function with a method for
	MArrayLM objects.

    o   
	New argument 'legacy' for diffSplice().

    o   
	diffSplice() now adjusts transcript-level p-values using the
	full Simes method, instead of a modified Simes method leaving
	out the largest p-value for each gene that has been used until
	now. This will cause the Simes p-values returned by
	diffSplice() to be slightly more conservative than before.

    o   
	diffSplice() now returns Bonferroni adjusted p-values as an
	alternative to Simes method.

    o   
	The 'gene.genes' data.frame returned by diffSplice() now has
	row names set to the gene IDs. Previously the last exon ID for
	each gene was used.

    o   
	diffSplice() now allows for exons with df.residual=0 and
	sigma=NA.

    o   
	Bug fix to diffSplice() when fitFDistUnequalDF1() was called
	with 'robust=TRUE', i.e., whenever 'robust=TRUE' and the number
	of transcripts differs between genes.

    o   
	Bug fix to genewise variance pooling in diffSplice() when the
	residual df are unequal. Previously the exon-wise variances
	were not weighted by df when pooling.

    o   
	New argument 'directional' for camera() and cameraPR().

    o   
	vooma() now allows missing values in both 'y' and 'predictor',
	provided there are no entirely missing rows and provided all
	non-NA y values have a non-NA predictor.

    o   
	voomaLmFit() now allows missing values in 'y' and 'predictor',
	provided there are no entirely missing rows and provided all
	non-NA y values have a non-NA predictor.

    o   
	voomaLmFit() now allows 'predictor' to be either a matrix or a
	column vector with genewise values.

    o   
	Edit voomaLmFit() help page. Add Li (2024) PhD Thesis as
	reference.

                 Changes in version 3.62.0 (2024-10-30)                 

    o   
	New function fitFDistUnequalDF1() for improved empirical Bayes
	hyperparameter estimation. The new function is an alternative
	to the long-standing limma functions fitFDist() and
	fitFDistRobustly().  The new function gives special attention
	to contexts where the df1 argument is unequal between cases or
	can include small fractional values, such as those resulting
	from edgeR's voomLmFit() or from the edgeR 4.0 quasi-likelihood
	pipeline.  The new function uses profile maximum likelihood
	instead of moment estimation to estimate df.prior, and so may
	be more accurate than fitFDist() or fitFDistRobustly() even
	when the df1 values are all equal. The new hyperpameter
	estimation will be used by default by eBayes(), treat() and
	squeezeVar() whenever the residual degrees of freedom are
	unequal, but users can request legacy behavior for those
	functions by setting 'legacy=TRUE'.

    o   
	New argument 'adaptive.span' for voomWithQualityWeights() and
	normalizeCyclicLoess(), with the same purpose as the same
	argument for voom(). If 'TRUE' then an optimal value for the
	span is chosen based on the number of genes in the dataset.
	voom() and voomWithQualityWeights() now return the chosen
	'span' as part of the output object if 'adaptive.span=TRUE'.

    o   
	contrasts.fit() now converts the coefficient name "(Intercept)"
	created automatically by model.matrix() to "Intercept", same as
	is done by makeContrasts(). This should avoid inconsistent
	coefficient names between the fitted model object and contrast
	matrices created by makeContrasts().

    o   
	New argument 'keep.EList' for voomaLmFit(), similar to the same
	argument for edgeR::voomLmFit(). The observation weights
	generated by voomaLmFit() are now stored only if
	'keep.EList=TRUE'.

    o   
	voomaByGroup() now uses the overall mean-variance trend for
	groups with only one sample, for which a separate trend is not
	estimable.

    o   
	Add Ravindra et al (2023) as a reference and Mengbo Li as an
	author to the voomaByGroup() help page.  Emphasize in the help
	details that only simple design matrices are supported by this
	function.

    o   
	Revise the eBayes/treat help page to further clarify the
	'legacy' and 'fc' arguments.

    o   
	Bug fix to voomaByGroup() to save variance plot parameters
	correctly when 'save.plot=TRUE'.

    o   
	Remove argument 'zero.weights' from the MArrayLM method for
	plotMD() and plotMA().

    o   
	Fix bug in the MArrayLM methods for plotMD() and plotMA(),
	which were attempting to access a 'weights' component of the
	fitted model object, analogously to what plotMD() does with the
	EList or MAList objects, even though MArrayLM objects do not
	contain a 'weights' component.

    o   
	Use of the stats package digamma() function replaced with
	statmod's logmdigamma() in fitFDist(), fitFDistUnequalDF1() and
	intraspotCorrelation().  Slight improvements to speed, accuracy
	and code simplicity, but results should remain the same to at
	least 13 significant figures.

                 Changes in version 3.60.0 (2024-05-01)                 

    o   
	The default settings for the 'small.n' and 'min.span' arguments
	of chooseLowessSpan() have been increased, increasing the
	chosen span value.

    o   
	New argument 'adaptive.span' for voom(). If 'TRUE', then
	chooseLowessSpan() is used to select an optimal 'span' value
	depending on the number of genes, same as is done for vooma(),
	voomaByGroup() and voomaLmFit().

    o   
	The plot information saved by voom() when 'save.plot=TRUE' now
	includes 'pch' and 'cex' plotting character settings.

    o   
	The default 'span' set by vooma() is increased slightly to the
	value given by 'chooseLowessSpan(ngenes, small.n=50,
	min.span=0.3, power=1/3)'. A new argument 'legacy.span' had
	been added to optionally restore the old default settings for
	'span' for users who want backward compatibility.

    o   
	vooma() argument 'covariate' renamed to 'predictor'.

    o   
	vooma() has been revised in several other ways to match the
	behavior of voom() more closely. The order of arguments has
	been adjusted to match voom() and lmFit(). A new argument
	'save.plot' has been added similar to the same argument for
	voom(). Changes to have also been made to the title and xlab
	for the variance trend plot when 'predictor' is non-NULL.

    o   
	New function voomaLmFit() with the same functionality as
	vooma() but which automates the estimation of sample weights
	and intrablock correlation from vooma(). It produces an
	MArrayLM fit object instead of an EList object. It is the
	analogous to edgeR::voomLmFit() but for continuous
	microarray-like data.

    o   
	Edits to the help pages for decideTests(), voom(),
	voomWithQualityWeights(), vooma() and "11RNAseq". Example added
	to the vooma() help page.

    o   
	Add RNA-seq to package description.

    o   
	Add Charity Law, Goknur Giner and Mengbo Li to author list in
	package description.

                 Changes in version 3.58.0 (2023-10-25)                 

    o   
	New argument 'covariate' for vooma() that allows the variance
	trend to depend on an extra covariate in addition to average
	log-expression. This allows vooma() to take account of any
	predictor that is correlated with the precision of each
	expression value.

    o   
	New argument 'group' to simplify the typical calling sequence
	for removeBatchEffect().  The 'group' argument provides an
	alternative and possibly simpler way to specify the
	experimental conditions to be preserved.

    o   
	treat() now works when there are NA coefficients. Previously it
	gave an error if any estimated coefficient was NA.

    o   
	Fix behaviour of topTable() with 'adjust.method=NULL' so that
	it gives "BH" adjustment as documented. Previously the argument
	was passed to p.adjust(), which gave "holm" adjustment.

    o   
	Convert Introduction vignette from Sweave/pdf from to
	Rmarkdown/html.  The Introduction vignette is also somewhat
	expanded.

    o   
	cameraPR() has been addeed to the '10GeneSetTests.Rd' help
	topic.

    o   
	The pdf limma User's Guide is now formally listed as a
	vignette.

    o   
	Non-user-visible changes: limma now imports statmod rather than
	suggesting it.  BiocStyle has been added to the Suggests field
	of DESCRIPTION.

                 Changes in version 3.56.0 (2023-04-25)                 

    o   
	Rename readSampleInfoFromGEO() to sampleInfoFromGEO().

    o   
	Add new argument 'p.value' for topGO() and topKEGG().

    o   
	Fix a problem with inconsistent pathway names from KEGG. Due to
	a change on the KEGG website, pathway names from
	getGeneKEGGLinks() have "path:" prefixes but pathway names from
	getKEGGPathwayNames() do not. To make the pathway names
	consistent, getGeneKEGGLinks() now removes the "path:" prefix.

    o   
	eBayes() now checks whether 'fit' is a list object before
	undertaking other tests.

    o   
	Revise voom.Rd to specify that y-values in voom plot are sqrt
	residual standard deviations.

    o   
	Update out-of-date URLs in the help pages and the User's Guide.
	Convert reference URLs to DOIs.

    o   
	Convert CITATION to use the newer bibentry() instead of
	citEntry().

                 Changes in version 3.54.0 (2022-11-02)                 

    o   
	New function goanaTrend() to estimate a covariate-dependent
	trend in the probability of differential expression for use in
	goana() and kegga() with 'trend=TRUE'. The trend estimated by
	goanaTrend() is squeezed slightly towards constancy to provide
	stability when the number of DE genes is small. The amount of
	squeezing decreases with the number of DE genes.
	
	goana() and kegga() now call goanaTrend() when the 'trend'
	argument is used. When 'plot=TRUE' the plot is now created by
	goanaTrend() instead of by barcodeplot().

    o   
	Rename argument 'prior.prob' to 'null.prob' in goana() and
	kegga().

    o   
	Update goana() and kegga() code to catch NA gene IDs or
	covariate values.

    o   
	goana() and kegga() no longer give an error when a trend is
	estimated but there are no DE genes.

    o   
	kegga() now uses https instead of http links when reading from
	rest.kegg.jp.

    o   
	Add new argument 'fc' to topTable() and topTableF().  Change
	default for 'lfc' to NULL instead of 0.

    o   
	lmFit() now checks explicitly for NAs in the design matrix.

    o   
	Update references listed on help pages to use DOIs instead of
	URLs.

                 Changes in version 3.52.0 (2022-04-27)                 

    o   
	New function readSampleInfoFromGEO().

    o   
	Allow the 'trend' argument of eBayes() to specify a general
	variance covariate.

    o   
	More detailed checking and error messages when the 'object'
	input to lmFit() is a data.frame.

    o   
	Improve checking for incorrectly specified 'contrasts' argument
	in contrasts.fit().

                 Changes in version 3.50.0 (2021-04-27)                 

    o   
	Improve help pages for fry() and barcodeplot().

    o   
	Revise Section 18.1.10 of User's Guide so that coloring of X
	and Y genes is consistent between plots.

    o   
	Fix bug in the MDS class method of plotMDS() (introduced in the
	previous release) when new 'dim.plot' values are set.

    o   
	Fix bug in read.idat() when 'annotation' contains NA values.

                 Changes in version 3.48.0 (2021-05-20)                 

New functionality

    o   
	Explicitly setting 'weights=NULL' in a call to lmFit() no
	longer over-rides the 'weights' value found in 'object'.
	Default settings in lmFit() changed from 'ndups=' and
	'spacing=1' to 'ndups=NULL' and 'spacing=NULL', although this
	doesn't change function behavior from a user point of view.

    o   
	A number of improvements to duplicateCorrelation() to make the
	results more robust and to make the interface consistent with
	lmFit().  duplicateCorrelation() sets 'weights' same as
	lmFit(). Setting 'weights=NULL' in the function call no longer
	overwrites weights found in 'object'.  duplicateCorrelation()
	now checks whether the block factor is spanned by the design
	matrix. If so, it returns intrablock correlations of zero with
	a warning. Previously this usage error was not specifically
	trapped and could lead to correlations that were or NA or close
	to 1 depending on floating point errors.
	duplicateCorrelation() now issues a simplified message when
	design is not of full rank and uses message() to do so instead
	of cat().  In terms of output, duplicateCorrelation() now
	bounds the genewise correlations away from the upper and lower
	bounds by 0.01 so that the correlation matrix will always be
	positive-definite.  There is also a fix to the value returned
	by duplicateCorrelation() when no blocks or duplicates are
	present.

    o   
	New argument 'fc' for treat() so that the fold-change threshold
	can optionally be specified on the fold-change scale rather
	than as a log2-fold-change.

    o   
	plotMDS() no longer calls cmdscale() but instead performs the
	necessary eigenvector computations directly. Proportion of
	variance explained by each dimension is now computed and is
	optionally added to the dimension labels.  The 'ndim' argument
	is now removed. All eigenvectors are now stored so that
	plotMDS.MDS does not need to recompute them when different
	dimensions are plotted.

    o   
	New arguments 'path' and 'bgxpath' for read.idat().
	read.idat() now checks for gzipped IDAT files and, if detected,
	gives an informative error message.  read.idat() now checks for
	existence of input files before calling illuminaio read
	functions.

Other code improvements

    o   
	The average log-expression column written by write.fit() now
	has column heading "AveExpr" to match the output from
	topTable().  The column was previously called "A".

Documentation

    o   
	Additional documentation for the 'design' argument of 'lmFit'
	using the term "samples" instead of "arrays" and mentioning
	that the design matrix defaults to 'object$design' when that
	component is not NULL.

    o   
	duplicateCorrelation() help page revised including new code
	example.

    o   
	Help page for voom() now explains that the design matrix will
	be set from the 'group' factor of the DGEList object if
	available.

    o   
	coolmap() help page now clarifies which heatmap.2() arguments
	are reserved and which can be included in the coolmap call.

Bug fixes

    o   
	Fix typo in voom() warning when negative counts are detected.

                 Changes in version 3.46.0 (2020-10-28)                 

New functionality

    o   
	New function chooseLowessSpan().

    o   
	fitFDist() with a non-NULL 'covariate' now fits a smoother
	trend (with fewer spline knots) than before unless there are at
	least 30 observations. This also affects squeezeVar() and
	eBayes() with 'trend=TRUE'.

    o   
	New argument 'output.style' to weightedLowess().

    o   
	write.fit() now outputs a blank column heading for the row
	names so that the number of column names in the delimited
	output file will agree with the number of columns (similar to
	write.csv in the base package).

Code improvements

    o   
	Subsetting and contrasts.fit() now work on MArrayLM objects
	even if the cov.coefficients component is absent.

    o   
	volcanoplot() now prompts user to run eBayes() if the object
	doesn't contain p-values.

    o   
	Add checks and more informative error messages to getEAWP() and
	lmFit() when the data object is missing, NULL or has zero rows.

    o   
	Subsetting for RGList, MAList, EListRaw, EList, MArrayLM or
	TestResults objects now accepts arguments other than 'i' or 'j'
	but ignores them without an error. This is relevant if a user
	adds a 'drop' argument by analogy with matrix subsetting.
	Previously that produced an error.

    o   
	Subsetting of TestResults now requires two arguments, same as
	all of the other data object classes listed above. Previously
	single index subsetting (for example object[i]) was allowed.

    o   
	Improved treatment of zero weights by weighted.median().

    o   
	More consistent use of rep.int(), rep_len() and rep()
	throughout the package.

    o   
	Replace NA with NA_real_ where appropriate.

    o   
	Add a message to topTableF() to warn that the function is
	obsolete and will be removed in a future version of limma.
	Remove usages of topTableF() from the User's Guide.

    o   
	Remove obsolete function toptable(), which has been officially
	deprecated in favor of topTable() since 1 Feb 2018.

Documentation

    o   
	Revise and expand the weightedLowess help page.

    o   
	Add more explanation about "heirarchical" method in the details
	section of the decideTests() help page.

    o   
	Add Note to voom help page to emphasise that voom is not an
	appropriate tool to analyse expresssion measures that have been
	normalized for library size.

    o   
	Revise the help page for plotMDS() to clarify that the function
	can produce PCA plots as well as PCoA plots.

    o   
	Add example to EList-class help page.

    o   
	Edits to the eBayes help page.

    o   
	Edit concept entries for help files (for reference manual
	index).

Bug fixes

    o   
	Revise write.fit() so that column names of the output file are
	correct when 'digits=NULL' and the 'fit' object contains only
	one coefficient column. Previously the same contrast name was
	repeated as the column name for the coefficients, t-statistics
	and p.values, making them hard to distinguish.

    o   
	Bug fix to arrayWeights() when 'y' contains NAs, the design
	matrix has several columns and some but not all genes have no
	residual df.

                 Changes in version 3.44.0 (2020-04-28)                 

New functionality

    o   
	Add new argument 'package' to changeLog(). changeLog() now
	works for any package rather than only for limma.

Code improvements

    o   
	Improved treatment of NA coefficients by contrasts.fit().
	contrasts.fit() has always removed coefficients that were NA
	because of singularities in the design matrix, but any extra NA
	coefficients caused by NA expression values would cause all the
	stdev.unscaled values returned by contrasts.fit() to be NA for
	those genes.  contrasts.fit() now returns non-NA coefficients
	and non-NA stdev.unscaled values if all the NA coefficients are
	multiplied by zero contrast multipliers.

    o   
	Speed improvement for contrasts.fit() if some input
	coefficients are not involved (have zero multipliers) in any of
	the contrasts.

    o   
	contrasts.fit() now preserves the 'pivot' component of the fit
	object instead of removing it.

    o   
	voom now checks explicitly for NA or negative counts and gives
	an informative error message.

    o   
	fitFDist() now allows a covariate trend even with fewer than 4
	useable observations. (Useable means positive residual df and
	finite variance and covariate values.)

    o   
	Internal code cleaned up to avoid partial matching of function
	arguments, attributes or list component names. The automatic
	package tests are now run with the warnPartialMatchArgs,
	warnPartialMatchAttr and warnPartialMatchDollar options all set
	to TRUE.

Documentation

    o   
	More explanation of 'covariates' argument to
	removeBatchEffects().

Bug fixes

    o   
	Fix bug in contrasts.fit() when some coefficients are NA due to
	NA expression values and the corresponding contrast multipliers
	are zero. The new code fixes the improvement originally
	introduced in limma 3.35.9. The new code will return non-NA
	contrasts if the NA coefficients all get 0 weight in the
	contrast. Previous code was correct if all genes had the same
	NA coefficients but could give an avoidable NA result if some
	genes had NA coefficients but the first gene did not.

    o   
	Improvements to subsetting MArrayLM objects by column.
	Previously the presence of non-estimable coefficients sometimes
	caused the cov.coefficient matrix to be subsetted incorrectly;
	that is now fixed. Subsetting zero columns is now allowed even
	when F-statistics are present.

    o   
	Fix to classifyTestsF() when one or more of the coefficients
	have zero variance. Previously the zero variance will introduce
	NAs into the correlation matrix and hence cause an error. This
	is now avoided. This also fixes eBayes() when one or more of
	the coefficients are identically zero (usually caused by an
	all-zero contrast).

                 Changes in version 3.42.0 (2019-10-30)                 

New functionality

    o   
	New head() and tail() methods for all limma data classes.

    o   
	New unique() and subsetting methods for TestResults objects.
	Previously a subsetted TestResults object became an ordinary
	numeric matrix, but now the TestResults class is preserved.
	Single index subsetting is also allowed but produces a numeric
	vector.

    o   
	New argument 'gene.weights' for fry() so as to match the
	arguments and behavior of mroast(). Previously gene weights
	could be input to fry() only through the 'index' argument.
	fry's mixed p-values now take account of gene weights.
	Previously gene weights were not used in fry's mixed p-value
	calculation.

    o   
	Add arguments 'block', 'correlation' and 'weights' to voom()
	and remove the '...' argument.

    o   
	Update the arguments of voomWithQualityWeights() to match the
	revisions to arrayWeights() in limma 3.40.0.  Add new argument
	'var.group'.

    o   
	New arguments 'xlab', 'ylab' and 'main' for plotFB(). The
	default plot title now includes the column name from the data
	object.  Default for 'pch' increased to 0.3.

    o   
	plotWithHighlights and plotMD.MArrayLM now gives special
	treatment to the case that 'status' is a TestResults object.

Code improvements

    o   
	roast() and mroast() now use less memory. Memory usage now
	remains bounded regardless of the number of rotations used.
	Both functions are faster than before when approx.zscore=TRUE.
	A new argument 'legacy' is added to allow users to turn these
	improvements off if they wish to reproduce numerical results
	from limma 3.40.0 exactly.  The default number of rotations
	'nrot' is increased from 999 to 1999.  A bug has been fixed for
	roast() and mroast() when 'index' is a character vector of
	geneids or rownames. Previously this usage failed.

    o   
	Complete rewrite of zscoreT(), which is now somewhat faster and
	offer two new options for the normalizing transformation. The
	new argument 'method' indicates which transformation is used
	when 'approx=TRUE'. The default approximation method is changed
	from "hill" to "bailey".  zscoreT() now allows NA values when
	'approx=TRUE' and works correctly for all valid df values.
	Previously 'approx=TRUE' returned NA results for 'df' infinite
	or <= 0.05. A simple robust approximation from Wallace (1959)
	has been introduced to handle very large or very small 'df'
	values. Previously 'approx=FALSE' treated any 'df' greater than
	10000 as infinite; this threshold is now raised to 1e300.

    o   
	tZScore() is slightly faster.

    o   
	All uses of the approx() function now set
	'ties=list("ordered",mean)', except for fitFDistRobustly()
	which uses 'ties=mean'.  The change was prompted by a change in
	R 3.6.0 whereby using the default for 'ties' generates a
	warning message whenever ties are present in 'x'. The new code
	gives the same results but is very slightly faster and avoids
	the warning message.  limma now depends on R >= 3.6.0 because
	of this change.

Documentation

    o   
	Update Yoruba case study in User's Guide to call voom() and
	duplicateCorrelation() twice each instead of once.

    o   
	Update Users Guide: update Rsubread reference, correct remarks
	about prior distribution for 1/sigma^2 in Section 13.2 and
	rerun the Yoruba and Pasilla case studies.

    o   
	Use "RNA-seq" and "ChIP-seq" consistently in the documentation
	instead of "RNA-Seq" and "ChIP-Seq".

Bug fixes

    o   
	Fix bug in barcodeplot() when 'index' or 'index2' are character
	vectors.

                 Changes in version 3.40.0 (2019-05-03)                 

    o   
	Major rewrite of arrayWeights() to improve speed and stability.
	The arrayWeightsSimple() function has been removed and its
	functionality incorporated into arrayWeights(). A new
	'var.group' argument has been added to simplify specification
	of the variance design matrix. The weights are now squeezed
	slightly towards unit and a new argument 'prior.n' has been
	added to control the prior weight with which the array weights
	are squeezed. arrayWeights() now chooses between the REML and
	gene-by-gene algorithms automatically by default. REML is
	chosen when there are no prior weights or missing values and
	gene-by-gene is used otherwise. arrayWeights() now checks for
	and skips over any genes with zero residual variances.

    o   
	voom() now checks for experiments that have no replication. In
	this case it now returns weights that are all 1, with an
	informative warning but no error. Two references have been
	added to the voom help page.

    o   
	classifyTests.Rd now focuses on nested F-tests. The function
	FStat() is now removed. It was a convenience wrapper for
	classifyTestsF() with fstat.only=TRUE but is not used often
	enough to justify itself. classifyTestsP() is no longer
	exported as it is not intended to be called by users. The
	function classifyTestsT() is now removed, having been
	superceded by more sophisticated multiple testing methods.

    o   
	contrasts.fit() now removes any test statistics or p-values
	found in the fit object. This avoids any potential mis-match
	between coefficients and test statistics if eBayes() has been
	run on the object previously.
	
	More details have been added to the warning about
	approximations in the contrasts.fit() help page.

    o   
	The old function ebayes(), which was deprecated a year ago in
	favor of eBayes(), is now removed.

    o   
	The fitted() and residuals() methods for MArrayLM objects now
	give an informative error message if the object contains
	contrasts instead of the original coefficients.

    o   
	Rewrite Filtering chapter of User's Guide.

    o   
	Add Research Fields to the biocViews entry in the package
	DESCRIPTION file.

                 Changes in version 3.38.0 (2018-10-31)                 

    o   
	New function plotExonJunc() to plot results from diffSplice().

    o   
	New function logsumexp().

    o   
	New argument hl.col for volcanoplot(), allowing users to
	specify the color for the gene names when highlight > 0.

    o   
	barcodeplot() no longer assumes that 'statistic' has unique
	names. Previously it returned an error if names(statistic)
	contained any duplicated values.

    o   
	The colors "blue", "red" and "yellow" used by coolmap() changed
	to "blue2", "red2" and "yellow2" when used in a color panel
	with white.

    o   
	goana.Rd now explains more explicitly that p-values are
	unadjusted for multiple testing.

    o   
	arrayWeights.Rd now mentions minimum dimensions for expression
	object.

    o   
	More advice on how to choose 'lfc' added to the treat() help
	page.

    o   
	Minor bug fix to the mixed p-value from roast() and mroast()
	when set.statistic="floormean".

    o   
	Bug fix for cumOverlap(), which was under-counting overlaps in
	some cases.

                 Changes in version 3.36.0 (2018-05-01)                 

    o   
	New arguments 'quote' and 'row.names' for write.fit().
	Write.fit() now outputs row.names by default, which previously
	were suppressed.

    o   
	coolmap() will now accept an arbitrary vector of colors. A new
	preset "whitered" panel is now also supported.

    o   
	In the past, contrasts.fit() always returned NA contrasts for
	genes with any NA fitted coefficients. contrasts.fit() will now
	ignore an NA coefficient if the contrast multiplier is zero for
	that coefficient.

    o   
	The treat() default for 'lfc' changed from lfc=0 to
	lfc=log2(1.2).

    o   
	kegga() and goana() now check whether a data.frame has been
	input by mistake and generates an error. Previously a
	data.frame value for 'de' was interpreted as a list of gene
	sets without any error.

    o   
	voomWithQualityWeights() now returns 'sample.weights' as a
	column of the 'targets' data.frame instead of as a separate
	vector.

    o   
	"TestResults" objects now include a 'labels' attribute,
	defaulting to c("Down","NotSig","Up").

    o   
	Functions ebayes() and toptable(), long ago replaced by
	eBayes() and topTable(), are now formally deprecated.

    o   
	Update the User's Guide case study that analyses Lrp- E. Coli
	samples and profiled by Affymetrix arrays.

    o   
	Update the Agilent single-channel case study in Section 17.4 of
	the Users' Guide to use the Agilent gIsWellAboveBG detection
	column.

    o   
	Comments added to voom.Rd and eBayes.Rd to clarify the
	relationship between limma-trend and voom.

    o   
	In the kegga help page, clarify default gene ID system used by
	kegga() when species="dme".

    o   
	Update wsva() help page to describe correct number of columns
	for output.

    o   
	bug fix for goana() when 'covariate' is specified and some of
	the 'universe' genes don't have GO annotation.

    o   
	Fix to how roast(), mroast() and fry() handle weights. The
	'weight' argument can now be a matrix, or a vector of length
	nrow(y), or a vector of length ncol(y). This allows the
	functions to accept precision weights, or gene weights, or
	sample weights.

                 Changes in version 3.34.0 (2017-10-31)                 

    o   
	read.idat() can now handle idat files in SNP format.

    o   
	New argument 'sort.by' for topSplice().

    o   
	diffSplice() now treats any NA geneid as a separate gene with
	one exon. Previously all NA geneids were treated as the same
	gene.

    o   
	Bug fixes for plotSplice() which, in some circumstances, was
	not highlight significant exons.

    o   
	Default value for 'style' in volcanoplot() changed to "p-value"
	instead of "p". This doesn't change the behavior of the
	function.

    o   
	volcanoplot() didn't work with MArrayLM objects produced by
	treat(). Now fixed.

    o   
	The gene.info.file argument of alias2SymbolUsingNCBI() will now
	optionally accept a data.frame instead of a file name.

    o   
	alias2SymbolUsingNCBI() now always produces a data.frame.
	Previously a single-column data.frame was returned as a vector.

    o   
	Bug fixes to camera() and cameraPR() when 'index' contains
	character row names.

    o   
	New argument 'restrict.universe' for the default kegga()
	method.  The default is now not to the restrict the universe to
	genes with KEGG annotation.

    o   
	goana.default() code is rewritten to more closely match
	kegga.default. Slight speed improvement. Prior probabilities
	are now computed using the restricted universe with GO
	annotation instead of the whole universe.

    o   
	Bug fix for kegga() when trend=TRUE or a prior.prob or
	covariate is specified. Previously the Down p-values were
	substantially too small and the Up p-values were too large.

    o   
	plotWithHighlights() checks whether 'status' is a factor and
	converts to character.

    o   
	Bug fixes for beadCountWeights(). Default is now set correct
	for 'design' and the function now works correctly when 'y' is
	an EList object contain bead standard errors but not standard
	deviations.

                 Changes in version 3.32.0 (2017-04-25)                 

    o   
	New function cameraPR(), which implemented a pre-ranked version
	of camera().

    o   
	New function alias2SymbolUsingNCBI(), which converts gene
	aliases or synonyms into official gene symbols using an NCBI
	gene-info file.

    o   
	New function wsva() for weighted surrogate variable analysis.

    o   
	New function coolmap(). This is essentially a wrapper for the
	heatmap.2() function in the ggplots package, but with sensible
	default settings for genomic log-expression data.

    o   
	decideTests() is now an S3 generic function with a default
	method and a method for MArrayLM objects. decideTests() now
	selects all null hypotheses as rejected if p.value=1.

    o   
	length() methods removed all limma data objects (objects of
	class EList, EListRaw, RGList, MAList or MArrayLM). length(x)
	will now return the number of list components in the object
	rather than the number of elements in the expression matrix.

    o   
	New argument 'style' for volcanoplot(). The default is now to
	use -log10(p-value) for the y-axis instead of the B-statistic.

    o   
	New argument 'xlab' for barcodeplot().

    o   
	New argument 'col' for plotSA(). plotSA() now longer plots a
	lowess curve trend, but if appropriate both high and low
	outlier variances are highlighted in a different color.

    o   
	Argument 'replace.weights' removed from
	voomWithQualityWeights().  The function now always produces an
	EList, similar to voom(). The default behavior of the function
	is unchanged.

    o   
	barcodeplot() now ranks statistics from low to high, instead of
	from high to low, following the usual style of axes in R plots.
	This means that left and right are now interchanged.

    o   
	plotSA() now plots quarter-root variances instead of
	log2(variances).

    o   
	Default for 'legend' argument of plotWithHighlights() changed
	from "topleft" to "topright".

    o   
	fitFDist() now estimates the scale by mean(x) when df2 is
	estimated to be Inf. This will make the results from eBayes()
	less conservative than before when df.prior=Inf.

    o   
	plotSA() now indicates, by way of an open plotting symbol, any
	points that have low robust df.prior values.

    o   
	Clearer error message from fitFDistRobustly() when some
	variances are zero.

    o   
	C functions are now registered using R_registerRoutines.

    o   
	Bug fix for contrastAsCoef() when there is more than one
	contrast.  Previously the coefficients for the transformed
	design matrix were correct only for the first contrast.

    o   
	Bug fix for kegga() when the universe is explicitly specified.

    o   
	Bug fix for fitFDistRobustly() when there is an extreme
	outlier.  Previously floating point underflow for the outlier
	p-value could cause an error.

    o   
	Bug fix to mroast(), which was ignoring 'geneid' argument.

    o   
	Bug fix to printHead() for arrays with 1 column.

                 Changes in version 3.30.0 (2016-10-18)                 

    o   
	New function cumOverlap() to analyse the overlap between two
	ordered lists.

    o   
	New function detectionPValues() to compute detection p-values
	from negative control probes.

    o   
	New function fitmixture() to estimate genewise fold changes and
	expression values from mixture experiments. Previously this
	funtion was only available as part of the illumina package
	available from http://bioinf.wehi.edu.au/illumina

    o   
	New function logcosh() to compute log(cosh(x)) accurately
	without floating underflow or overflow.

    o   
	The default settings for the 'inter.gene.cor' and 'use.neg.cor'
	arguments of camera() have been changed. camera() now uses by
	default a preset value for the inter-gene correlation. This has
	the effect that it tends to rank highly co-regulated,
	biologically-interpretable more highly than before.

    o   
	New flexibility for the roast() and mroast() functions, similar
	to that previously implemented for fry(). The index vector for
	each gene set can now be a data.frame, allowing each gene set
	to have its own set of gene weights. The indices can now
	optionally be a vector of gene names instead of a vector of
	indices. roast() and mroast() now support the robust empirical
	Bayes option of squeezeVar(). roast() and mroast() can now
	accept, via '...', any argument that would be normally passed
	to lmFit() or eBayes().

    o   
	Slight change to the standardize="posterior.sd" method for
	fry().

    o   
	goana(), alias2Symbol() and alias2SymbolTable() now work for
	any species for which an Entrez Gene based organism package
	exists.

    o   
	The 'species' argument of kegga() can now accept any
	Bioconductor species abbreviation.

    o   
	topGO() now breaks ties by the number of genes in the GO Term
	and by the name of the Term if the p-values are equal. (This is
	the same behavior as topKEGG.)

    o   
	New argument 'plot' for plotMDS(), to optionally allow an MDS
	object to be returned without making a plot.

    o   
	New arguments 'annotation' and 'verbose' for read.idat().  The
	first of these to allows users to read any required columns
	from the manifest file.

    o   
	New arguments 'pch.y' and 'pch.z' for plotRLDF.

    o   
	Unnecessary argument 'design' removed from fitted.MArrayLM.

    o   
	normalizeBetweenArrays() now checks whether the input 'object'
	is a data.frame, and converts to a matrix if possible.

    o   
	duplicateCorrelation() now expands weights using
	expandAsWeights(), making it consistent with lmFit().

    o   
	The lowess line drawn by plotSA() is now more robust with
	respect to NA variances.

    o   
	More informative error message from voom() when there is only
	one row of data.

    o   
	More informative error message from getEAWP() and lmFit() when
	'object' is a non-normalized data object.

    o   
	Update Phipson et al (2016) reference for robust empirical
	Bayes.

    o   
	Bug fix to fitFDistRobustly(), which in some circumstances was
	trying to save extra (undocumented) results that had not been
	computed.

    o   
	Bug fixes for fry() with robust=TRUE or when 'index' has NULL
	names.

    o   
	Bug fix to propTrueNull() when method="hist" and all the
	p-values are less than 1/nbins.

    o   
	Bug fix to alias2Symbol() with expand.symbol=TRUE.

                 Changes in version 3.28.0 (2016-05-04)                 

    o   
	Improved capabilities and performance for fry(). fry() has two
	new arguments, 'geneid' and 'standardize'. The index argument
	of fry() can now be a list of data.frames containing
	identifiers and weights for each set. The options introduced by
	the standardize argument allows fry() to be more statistically
	powerful when genes have unequal variances. fry() now accepts
	any arguments that would be suitable for lmFit() or eBayes().
	The 'sort' argument of fry() is now the same as for mroast().

    o   
	roast(), mroast(), fry() and camera() now require the 'design'
	matrix to be set. Previously the design matrix defaulted to a
	single intercept column.

    o   
	Two changes to barcodeplot(): new argument 'alpha' to set
	semitransparency of positional bars in some circumstances; the
	default value for 'quantiles' is increased slightly.

    o   
	kegga() has several new arguments and now supports any species
	supported by KEGG. kegga() can now accept annotation as a
	data.frame, meaning that it can work from user-supplied
	annotation.

    o   
	New functions getGeneKEGGLinks() and getKEGGPathwayNames() to
	get pathway annotation from the rest.kegg website.

    o   
	topKEGG() now breaks tied p-values by number of genes in
	pathway and by name of pathway.

    o   
	goana() now supports species="Pt" (chimpanzee).

    o   
	plotRLDF() now produces more complete output and the output is
	more completely documented. It can now be used as a complete
	LDF analysis for classification based on training data. The
	argument 'main' has been removed as an explicit argument
	because it and other plotting arguments are better passed using
	the ... facility.  New arguments 'ndim' and 'plot' have been
	added. The first allows all possible discriminant functions to
	be completed even if only two are plotted. The second allows
	dicriminant functions to be computed without a plot.
	
	plotRLDF() also now uses squeezeVar() to estimate how by how
	much the within-group covariance matrix is moderated. It has
	new arguments 'trend' and 'robust' as options to the empirical
	Bayes estimation step. It also has new argument 'var.prior' to
	allow the prior variances to be optionally supplied. Argument
	'df.prior' can now be a vector of genewise values.

    o   
	New argument 'save.plot' for voom().

    o   
	diffSplice() now returns genewise residual variances.

    o   
	removeExt() has new 'sep' argument.

    o   
	Slightly improved algorithm for producing the df2.shrunk values
	returned by fitFDistRobustly(). fitFDistRobustly() now returns
	tail.p.value, prob.outlier and df2.outlier as well as
	previously returned values. The minimum df.prior value returned
	by eBayes(fit, robust=TRUE) may be slightly smaller than
	previously.

    o   
	tmixture.vector() now handles unequal df in a better way. This
	will be seen in slightly changed B-statistics from topTable
	when the residual or prior df are not all equal.

    o   
	If a targets data.frame is provided to read.maimages() through
	the 'files' argument, then read.maimages() now overwrites its
	rownames on output to agree with the column names of the RGList
	object.

    o   
	More explicit handling of namespaces.  Functions needed from
	the grDevices, graphics, stats and utils packages are now
	imported explicitly into the NAMESPACE, avoiding any possible
	masking by other packages.  goana(), alias2Symbol(),
	alias2SymbolTable() now load the name spaces of GO.db the
	relevant organism package org.XX.eg.db instead of loading the
	packages.  This keeps the user search path cleaner.

    o   
	Various minor bug fixes and improvements to error messages.

                 Changes in version 3.26.0 (2015-10-14)                 

    o   
	New functions kegga() and topKEGG() to conduct KEGG pathway
	over-representation analyses.  kegga() is an S3 generic
	function with a method for MArrayLM fitted model objects as
	well a default method.  It uses the KEGGREST package to access
	up-to-date KEGG pathways using an internet connection.

    o   
	goana() with trend now chooses the span of the tricube smoother
	based on the number of differentially expressed genes. Larger
	spans give smoother trends and are used for smaller numbers of
	genes. Arguments 'species' and 'plot' are no longer part of
	goana.MArrayLM() and are instead passed if present in a call to
	goana.default().

    o   
	topGO() has a new argument 'truncate.term' to limit number of
	characters appearing in a column of the output data.frame.

    o   
	Improved power for the romer() function. The empirical Bayes
	shrinkage of the residuals, removed on 4 April, has been
	re-instated in a corrected form. It can optionally be turned
	off using the 'shrink.resid' argument.

    o   
	camera() has a new argument inter.gene.cor. This allows a
	preset inter gene correlation to be set for each test test,
	resulting in potentially less conservative tests.  camera() no
	longer gives NA results when a gene has a residual variance
	exactly zero.

    o   
	mroast() now sorts significant gene sets by proportion of genes
	changing as well as by p-value and set size. When p-values are
	equal, sets with a higher proportion of changing genes will now
	rank higher in ordered results.  The contrast argument of
	roast() can now optionally be a character string giving the
	name of a column of the design matrix.

    o   
	fry() now produces "mixed" (non-directional) p-values and FDRs
	as well as directional p-values and FDRs.  Bug fix for fry()
	when the gene set has a small number of genes.

    o   
	camera(), fry(), mroast() and romer() now give more informative
	error messages when the index list is empty.

    o   
	Speedup for ids2indices().

    o   
	tricubeMovingAverage() has new argument 'power' and old
	argument 'full.length' is removed.  tricubeMovingAverage() now
	checks whether span is correctly specified. It now gives
	identical results for any span>=1 or any span<=0.

    o   
	lmFit() and friends now always produce an output component
	'rank' that returns the column rank of the design matrix.
	Previously it depended on the options used whether this
	component was given.

    o   
	lmFit() now assumes that if the 'object' of expression values
	is a simple vector, that it represents a single gene rather
	than a single sample.

    o   
	lmFit() now always treats infinite expression values as NA. In
	the past, this was done somewhat inconsistently.

    o   
	Checking for NA coefficients in lmFit() is now done more
	efficiently, meaning that lmFit() is now faster on large
	datasets.

    o   
	More informative error message from lmscFit() when correlation
	is NA.

    o   
	getEAWP() now works on all eSet objects, not just
	ExpressionSet, provided there is an data element called
	"exprs".  This allows all the linear modelling functions to
	handle general eSet objects.

    o   
	plotMD() can now accept arguments 'array' or 'coef' as
	appropriate as synonyms for 'column'. This may help users
	transitioning from plotMA ot plotMD.

    o   
	Arguments hi.pch, hi.col and hi.cex of plotWithHighlights()
	renamed to hl.pch, hl.col and hl.cex. ('hl' is short for
	'highlight'.)

    o   
	New 'tolerance' argument for read.idat() to allow manifest and
	idat to differ by a certain number of probes

    o   
	The 'genes' argument of controlStatus() now accepts EListRaw or
	Elist objects.

    o   
	All data classes (EListRaw, EList, RGList, MAList, MArrayLM)
	now require two arguments for subsetting. This restores the
	behavior in limma version 3.19.10 and earlier. In limma 3.19.11
	through 3.25.13, subsetting by one argument y[i] was equivalent
	to y[i,].  This will now give an error message.

    o   
	The dimnames<- method for EListRaw objects now sets rownames
	for the background matrix Eb as well as for the foreground
	matrix E.

    o   
	avearrays() now gives a more informative error message if input
	argument 'x' is not a matrix.

    o   
	auROC() now allows for tied stat values.

    o   
	Bug fix to write.fit() when method="global" and fit contains
	more than one column.

                 Changes in version 3.24.0 (2015-04-17)                 

    o   
	Limma review article (Ritchie et al, Nucleic Acids Research,
	2015) is now published, and becomes the primary citation for
	limma. References in User's Guide, help files and CITATION have
	been updated to refer to this article.

    o   
	New function plotMD() for mean-difference plots. This will take
	over the functionality of the plotMA() function.

    o   
	mdplot() has new arguments 'columns' and 'main'.

    o   
	Arguments 'pch', 'cex' and 'col' of plotWithHighlights()
	renamed to 'hi.pch', 'hi.cex' and 'hi.col'. Improved help page
	for plotWithHighlights().

    o   
	plot() methods removed for EList, MAList and MArrayLM objects.
	Use plotMD() instead.

    o   
	New function fry() provides a fast version of mroast() when
	there is little heteroscedasticity between genes.

    o   
	Minor change to mroast() output so that FDR values are never
	smaller than p-values, even when mid-p-values are used.

    o   
	camera(), roast(), mroast() and romer() now give a warning if
	any arguments found in ... are not used.

    o   
	romer() is now an S3 generic function. Speed improvements for
	romer() when the "mean" or "floormean" set statistics are used.
	The empirical Bayes shrinkage of the residuals, introduced 5
	October 2009, has been removed - this means that romer()
	results will revert to being somewhat more conservative.

    o   
	topGO() can now sort gene ontology results by several p-value
	columns at once, using the minimum of the columns. The default
	is now to sort results using all the p-value columns found in
	the results instead of just by the first column.

    o   
	goana() has new arguments 'plot' and 'covariate'. The plot
	argument allows users to view any estimated trend in the
	genewise significance values. The help files goana.Rd and
	goana.MArrayLM.Rd are consolidated into one file.

    o   
	plotDensities() has a new argument 'legend', allowing user to
	reposition the legend.

    o   
	voomWithQualityWeights() has a new argument 'col', allowing the
	barplot of sample weights to be colour-coded.

    o   
	Improvements and bug fixes to plotMDS(). plotMDS now stores
	'axislabel', depending on the method used to compute distances,
	and uses this to make more informative axis labels. plotMDS now
	traps problems when the distances are all zero or if one or
	more of the dimensions are degenerate. Also, a bug when
	gene.selection="common" and top=nrow(x) has been fixed.

    o   
	The arguments for predFCm() have been renamed. Old argument
	'VarRel' replaced by logical argument 'var.indep.of.fc'. Old
	argument 'prop' replaced by 'all.de'. New argument
	'prop.true.null.method' passes through method to
	propTrueNull().

    o   
	vennDiagram() now fills circles with specified colors.

    o   
	plotMA() now has a method for EListRaw objects.

    o   
	voomWithQualityWeights() now stores the sample weights in the
	output EList object.  The values stored in $weights are
	unchanged, they are still the combined observation and sample
	weights.

    o   
	nec() and neqc() now remove the background Eb values if they
	exist in the EListRaw object.

    o   
	Acknowledgements edited in User's Guide.

    o   
	fix URLs for a number of references in help pages.

    o   
	Improvements to lowess C code.

    o   
	When loading suggested packages within function calls, usages
	of require() have been converted to requireNamespace() wherever
	possible. Functions from suggested packages are called using
	'::'.

    o   
	topTable() now gives an information error message if eBayes()
	or treat() have not already been run on the fitted model
	object.

    o   
	genas() now gives an error message when applied to fitted model
	for which the coefficient correlations are gene-specific.

    o   
	Fix a bug in the MAList method for plotDensities that was
	introduced with the use of NextMethod() in version 3.21.16.

                 Changes in version 3.22.0 (2014-10-14)                 

    o   
	New functions goana() and topGO() provide gene ontology
	analyses of differentially genes from a linear model fit. The
	tests include the ability to adjust for gene length or
	abundance biases in differential expression detection, similar
	to the goseq package.

    o   
	Improvements to diffSplice. diffSplice() now calculates Simes
	adjusted p-values for gene level inferences, in addition to the
	exon level t-tests and gene level F-tests. topSplice() now has
	three ranking methods ("simes", "F" or "t"), with "simes" now
	becoming the default. diffSplice() also has a new argument
	'robust' giving access to robust empirical Bayes variance
	moderation.

    o   
	New function plotExons() to plot log-fold-changes by exon for a
	given gene.

    o   
	New function voomWithQualityWeights() allows users to estimate
	sample quality weights or allow for heteroscedasticity between
	treatment groups when doing an RNA-seq analysis.

    o   
	Improvement to arrayQualightyWeights(). It now has a new
	argument 'var.design' which allows users to model variability
	by treatment group or other covariates.

    o   
	Improved plotting for voomaByGroup().

    o   
	barcodeplot() can now plot different weights for different
	genes in the set.

    o   
	Improvements to roast() and mroast(). The directional (up and
	down) tests done by roast() now use both the original rotations
	and their opposite signs, effectively doubling the number of
	effective rotations for no additional computational cost. The
	two-sided tests are now done explicitly by rotation instead of
	doubling the smallest one-sided p-value. The two-sided p-value
	is now called "UpOrDown" in the roast() output. Both functions
	now use a fast approximation to convert t-statistics into
	z-scores, making the functions much faster when the number of
	rotations or the number of genes is large. The contrast
	argument can now optionally be a character string giving a
	column name of the design matrix.

    o   
	zscoreT() can optionally use a fast approximation instead of
	the slower exact calculation.

    o   
	symbols2indices() renamed to ids2indices().

    o   
	Improvements to removeBatchEffect(). It can now take into
	account weights and other arguments that will affect the linear
	model fit. It can now accept any arguments that would be
	acceptable for lmFit(). The behavior of removeBatchEffect()
	with design supplied has also changed so that it is now
	consistent with that of lmFit() when modelling batches as
	additive effects. Previously batch adjustments were made only
	within the treatment levels defined by the design matrix.

    o   
	New function plotWithHighlights(), which is now used as the
	low-level function for plotMA() and plot() methods for limma
	data objects.

    o   
	The definition of the M and A axes for an MA-plot of single
	channel data is changed slightly. Previously the A-axis was the
	average of all arrays in the dataset - this has been definition
	since MA-plots were introduced for single channel data in April
	2003. Now an artificial array is formed by averaging all arrays
	other than the one to be plotted. Then a mean-difference plot
	is formed from the specified array and the artificial array.
	This change ensures the specified and artificial arrays are
	computed from independent data, and ensures the MA-plot will
	reduce to a correct mean-difference plot when there are just
	two arrays in the dataset.

    o   
	plotMDS() can now optionally plot samples using symbols instead
	of text labels. It no longer has a 'col' argument, which
	instead is handled by ....

    o   
	vennDiagram() now supports circles of different colors for any
	number of circles. Previously this was supported only up to
	three sets.

    o   
	getEAWP() will now find a weights matrix in an ExpressionSet
	object if it exists.

    o   
	update to helpMethods().

    o   
	Substantial updates to the two RNA-seq case studies in the
	User's Guide. In both cases, the short read data has been
	realigned and resummarized.

    o   
	Improvements to many Rd files. Many keyword entries have been
	revised. Many usage and example lines been reformated to avoid
	over long lines.

    o   
	biocViews keywords updated.

    o   
	Subsetting columns of a MArrayLM object no longer subsets the
	design matrix.

    o   
	Bug fix for read.maimages: default value for 'quote' was not
	being set correctly for source="agilent.mean" or
	source="agilent.median".

    o   
	Bug fix to topTableF() and topTable(). The ordering of Amean
	values was sometimes incorrect when sorting by F-statistic and
	a lfc or p.value filter had been set.

    o   
	Bug fix to read.ilmn() when sep=",".

                 Changes in version 3.20.0 (2014-04-12)                 

    o   
	New functions diffSplice(), topSplice() and plotSplice()
	provide functionality to analyse differential splicing using
	exon-level expression data from either microarrays or RNA-seq.

    o   
	New Pasilla case study added to User's Guide, demonstrating
	differential splicing analysis of RNA-seq data.

    o   
	new function weightedLowess() which fits a lowess curve with
	prior weights. Unlike previous implementations of lowess or
	loess, the weights are used in calculating which neighbouring
	points to include in each local regression as well as in the
	local regression itself.

    o   
	weightedLoess() now becomes the default method used by
	loessFit() to fit the loess curve when there are weights. The
	previous locfit and loess() methods are offered as options.

    o   
	linear model fit functions lm.series(), mrlm.series() and
	gls.series() no longer drop the dimensions of the components of
	the fitted object when there is just coefficient or just one
	gene. Previously this was done inconsistently in some cases but
	not others. Now the matrix components always keep dimensions.

    o   
	The functions lmFit(), eBayes() and tmixture.vector() now work
	even when there is just one gene (one row of data).

    o   
	New function subsetListOfArrays(), which is used to simplify
	the subsetting code for RGList, MAList, EList, EListRaw and
	MArrayLM objects.

    o   
	new function tricubeMovingAverage() for smoothing a time
	series.

    o   
	barcodeplot() has a new option to add enrichment worms to the
	plot, making use of tricubeMovingAverage().

    o   
	New plot() methods for RGList, MAList, EList and MArrayLM class
	objects. In each case, this produces a similar result to
	plotMA(). When using plot() or plotMA() on an MArrayLM object,
	the column is now specified by the 'coef' argument instead of
	by 'array'.

    o   
	plotMA3by2() now works on single channel data objects as well
	as on MAList objects.

    o   
	New function read.idat() to read files from Illumina expression
	beadarrays in IDAT format.

    o   
	The ctrlpath argument of read.ilmn() now defaults to the same
	as path for regular probes. This means that only one path
	setting is required if the regular and control probe profiles
	are in the same directory.

    o   
	read.ilmn() now sets the same probe IDs as rownames for both
	the expression matrix E and the annotation data.frame genes,
	providing that the probe IDs are unique.

    o   
	beadCountWeights() can now work with either probe-wise standard
	errors or probe-wise standard deviations.

    o   
	treat() has new arguments robust and winsor.tail.p which are
	passed through to robust empirical Bayes estimation.

    o   
	topTreat() now includes ... argument which is passed to
	topTable().

    o   
	topTable() with confint=TRUE now produces confidence intervals
	based on the t-distribution instead of on the normal
	distribution. It also now accepts a numeric value for the
	confint argument to specify a confidence level other the
	default of 0.95.

    o   
	topTable() will now work on an MArrayLM fit object that is
	missing the lods component, for example as produced by treat().

    o   
	roast() and mroast() now permit array weights and observation
	weights to both be specified.

    o   
	camera(), roast() and mroast() now use getEAWP() to interpret
	the data object. This means that they now work on any class of
	data object that lmFit() will.

    o   
	romer() now uses propTrueNull(method="lfdr") instead of
	convest(). This makes it substantially faster when the number
	of genes is large.

    o   
	genas() now uses fit$df.total from the MArrayLM object. This
	prevents df.total from exceeding the total pooled residual df
	for the dataset. The genas() results will change slightly for
	datasets for which df.prior was very lage.

    o   
	plotDensities() is now an S3 generic function with methods for
	RGList, MAList, EListRaw and EList objects.

    o   
	plotFB is now an S3 generic function with methods for RGList
	and EList data objects.

    o   
	New topic help pages 10GeneSetTests.Rd and 11RNAseq.Rd. The
	page 10Other.Rd is deleted. All topic help pages are now listed
	under 'See also' in the package introduction page accessible by
	?limma.

    o   
	avereps() was never intended to be applied to RGList or
	EListRaw objects. It now gives an error when applied to these
	objects instead of returning a matrix of questionable value.

    o   
	Bug fix: fitFDistRobustly() was failing when there were missing
	values or zero df values and covariate was NULL.

    o   
	Bug fix: vennDiagram() wasn't passing extra arguments (...) to
	plot() when the number of sets was greater than 3.

    o   
	Bug fix to topTreat(). Rownames were incorrectly ordered when
	p<1.

    o   
	bug fix to genas(), which was not handling vector df.prior
	correctly when the fit object was generated using robust=TRUE.

    o   
	bug fix to squeezeVar(). Previously there was an error when
	robust=TRUE and trend=FALSE and some of the estimated df.prior
	were infinite.

    o   
	bug fix to topTable() and topTableF() when sorting by
	F-statistic combined with p-value or lfc cutoffs.

                 Changes in version 3.18.0 (2013-10-15)                 

    o   
	new function beadCountWeights() to estimate quantitative
	weights from the bead counts for each probe for Illumina
	BeadArrays.

    o   
	New function contrastAsCoef(), which reforms a design matrix so
	that one or more specified contrasts become coefficients. This
	function is called by roast().

    o   
	plotMA() is now an S3 generic function.

    o   
	The legend argument to plotMA() can now take a character value
	giving the position to place the legend.

    o   
	toptable(), topTable() and topTreat() now preserve the rownames
	of the fit object, unless the fit object has duplicated names,
	in which case the rownames are copied to the ID column. Empty
	rownames are replaced with 1:nrow(fit).

    o   
	read.ilmn() no longer adds the probe IDs to the gene annotation
	data.frame, leaving them instead as rownames of the expression
	matrix. It longer creates a targets file since the sample names
	are already preserved as column names of the expression matrix.

    o   
	loessFit() now uses the locfit.raw in the locfit package when
	weights are provided instead of loess in the stats package. The
	function now runs very efficiently even on very long data
	vectors. The output results will change slightly when weights
	are provided.

    o   
	voom() now outputs lib.size as a column of targets instead of
	as a separate component.

    o   
	cbind for EList and EListRaw objects now recognizes a design
	matrix if it is present.

    o   
	plotMDS() now checks explicitly that there are at least 3
	samples to plot.

    o   
	normexp.fit.detection.p() now tolerates some non-monotonicity
	in the detection p-pvalues as a function of expression.

    o   
	fitFDistRobustly() now uses a smoother for the smallest
	df.prior values. This may result in smaller tail values than
	before when a group of input x values appear to be outliers but
	the largest value is not individually a stand-out value.

    o   
	New merge methods for EList and EListRaw objects.

    o   
	topTable() and treat() now give more informative error messages
	when the argument fit is not a valid MArrayLM object.

    o   
	roast() now calls mroast() if the index vector is a list. Bug
	fix to mroast(), which had been ignoring the weights.

    o   
	Updates to genas() function. argument chooseMethod renamed to
	subset and option "n" renamed to "all".  Function now returns
	NA results and a message when no genes satisfy the criterion
	for inclusion in the analysis. Some editing of help page and
	streamlining of code.

    o   
	Roles of contributors now specified in author field of
	DESCRIPTION file using standard codes.

    o   
	Additions and updates to references in the help pages. Removed
	defunct Berkeley Press links to published Smyth (2004) article
	in several Rd files. Replacing with link to Preprint. Added
	link to Phipson (2013) thesis in two Rd files. Add Majewski et
	al reference to genas.Rd. Add Phipson et al and Sartor et al
	references to squeezeVar.Rd. Add Phipson et al reference to
	eBayes.Rd. Update lmscFit and voom references.

    o   
	Update mammmary stem cell case study in User's Guide. As well
	as reflecting changes to read.ilmn() and topTable(), this now
	demonstrates how to find signature genes for particular cell
	type.

    o   
	documentation about rownames and column names and the use of
	rownames(fit) and colnames(fit) added to lmFit.Rd.

    o   
	improvements to help pages for data classes.

    o   
	Edits to normalizeBetweenArrays help page (i) to further
	clarify which normalization methods are available for
	single-channel data and which are available for two-color data
	and (ii) to give a cross citation to the neqc() function for
	Illumina BeadChips.

    o   
	Edits to voomaByGroup help page.

    o   
	duplicateCorrelation() now uses the weights matrix when block
	is set. Previously the weights were ignored when block was
	used.

    o   
	Bug fix to subsetting for MArrayLM objects: the df.total
	component was not being subsetted.

    o   
	bug fix to eBayes(robust=TRUE) when some of the df.prior values
	are infinite.

    o   
	Bug fix to ebayes(), which was not passing the 'robust'
	argument correctly on to squeezeVar().

    o   
	Bug fix to fitFDistRobustly(), which affected the estimated
	scale when df2 is estimated to be Inf.

                 Changes in version 3.16.0 (2013-04-04)                 

    o   
	New section in User's Guide on time course experiments with
	many time points. The RNA-seq case study in User's Guide has
	also been revised.

    o   
	Improvements to various help pages including read.maimages.Rd,
	squeezeVar.Rd, fitFDist.Rd, trigammaInverse.Rd,
	normalizeRobustSpline.Rd, genas.Rd and roast.Rd. Previously the
	meaning of source="agilent" was mis-stated in read.maimages.Rd.

    o   
	New robust method for estimating the empirical Bayes prior,
	called by specifying robust=TRUE in the call to eBayes(). When
	this is TRUE the output df.prior is now a vector instead of a
	scalar.

    o   
	New function fitFDistRobustly() estimates the parameters of a
	scaled F-distribution robustly using Winsorized values. Outlier
	observations receive smaller values for df.prior than
	non-outliers. This permits robust methods for squeezeVar(),
	ebayes() and eBayes(), all of which now have a new argument
	wins.tail.p to specify the tail proportions for Winsorizing.

    o   
	fitFDist() now permits infinite values for the covariate. It
	also gracefully handles cases where the covariate takes only a
	small number of distinct values. Similarly for eBayes() and
	squeezeVar() that call fitFDist().

    o   
	All the functions that perform gene set tests have been revised
	to make the input and output formats more consistent.
	
	roast(), mroast() and camera() are now S3 generic functions,
	with methods for EList and MAList objects.
	
	The order of arguments has been changed for roast(), mroast()
	and camera() so that the first argument is now y.
	
	All functions that perform gene sets now use the argument
	'index' to specify which genes are included in the test set.
	Previously this argument was called 'iset' for roast() and
	romer() and 'indices' for camera().
	
	camera() and mroast() now produce a data.frames. Instead of
	separate up and down p-value columns, there is now a two-sided
	p-value and a column indicating direction of change.  There are
	new columns giving FDR values and the number of genes in each
	set. There is a new argument 'sort' to indicate whether output
	results should be sorted by p-value.
	
	mroast() has a new argument 'weights' for observational
	weights, to bring it into line with roast(),

    o   
	vennDiagram() can now plot up to five sets (previously limited
	to three).

    o   
	genas() now optionally draws a plot in which ellipses are used
	to represent the technical and biological components of
	correlation. It also now has the ability to automatically
	select which probes are used for the correlation analysis, and
	a new argument controls the method used for this selection.

    o   
	New options for the method argument of propTrueNull().

    o   
	New functions vooma() and voomaByGroup() for computing
	precision weights based on a mean-variance trend. vooma() is
	similar to voom() but for microarray data instead of RNA-Seq.
	voomaByGroup() allows different groups to have systematically
	different variances.

    o   
	New function predFCm() to compute predictive (shrunk) log fold
	changes.

    o   
	New function fitGammaIntercept() for estimating the intercept
	of a gamma glm with an offset. Used by genas().

    o   
	New function zscoreHyper() for computing z-score equivalents of
	deviates from a hypergeometric distribution.

    o   
	New function qqf() for qq-plots relative to an F-distribution.

    o   
	normalizeWithinArrays() with method="robustspline" now longer
	requires the layout argument to be set. The layout argument for
	normalizeRobustSpline() now defaults to a single print-tip
	group.

    o   
	fitFDist() now coerces degrees of freedom df1 below 1e-15 to
	zero.

    o   
	Due to changes in R, loessFit() no longer makes direct calls to
	foreign language code in the stats package, and instead calls R
	functions. Unfortunately, this makes loessFit() about 25-30%
	slower than previously when weights are used.

    o   
	Bug fix to read.maimages(), which was not accepting
	source="agilent.mean".

    o   
	Bug fix for contrasts.fit() when the covariance matrix of the
	coefficients (cov.coefficients) is not found in the fitted
	model object. This situation doesn't arise using any of the
	standard limma analysis pipelines.

    o   
	Bug fix to lmscFit() when the residual df = 1.

    o   
	Bug fix to readTargets() to avoid warning message when
	targets$Label is used to set row names but targets$Label
	contains duplicated entries.

                 Changes in version 3.14.0 (2012-10-02)                 

    o   
	limma license upgraded to GPL (>=2) instead of LGPL to match R
	itself.

    o   
	Many updates to the User's Guide.  Sections have been added on
	reading single channel Agilent and Illumina data. The chapter
	on experimental designs has been split into three chapters on
	single-channel, common reference and two-color designs
	respectively. The material on the fixed effect approach to
	technical replication has been deleted. There are new sections
	on nested interactions for factorial designs and on multi-level
	designs.

    o   
	The links to the Apoa1, Weaver and Bob1 datasets in the User's
	Guide have been updated to help users download the data
	themselves if they wish to repeat the case study analyses.

    o   
	The help page for camera() now cites published paper Wu and
	Smyth (NAR, 2012). In view of the results of this paper, the
	claim is no longer made on help page for geneSetTest() that
	genes might be treated as independent when the experimental
	units are genetically identical mice.

    o   
	Minor edits to CITATION file.

    o   
	New function propTrueNull() for fast estimation of the
	proportion of true null hypotheses from a vector of p-values.

    o   
	New function zscore() to compute z-score equivalents for
	deviates from any continuous distribution. Includes the
	functionality of the older functions zscoreGamma() and
	zscoreT() as special cases.

    o   
	roast() now accepts observation level weights, through a new
	argument 'weights'.

    o   
	loessFit() now applies minimum and maximum bounds by default to
	avoid zero or infinite weights. Equal weights are now treated
	as if the weights were NULL, even all zero weights, so that the
	lowess code is called instead of the loess code.

    o   
	When there are no weights, loessFit() now extracts residuals
	directly from the C code output instead of computing in R.

    o   
	fitFDist() now permits missing values for x or zero values for
	df1 even when there is a covariate. This means that
	squeezeVar() and eBayes() now work with trends even when not
	all the data values are informative.

    o   
	New argument 'file' for convest(), implementing edits
	contributed by Marcus Davy. Arguments doplot and dereport
	renamed to 'plot' and 'report'.

    o   
	Two improvements for plotMDS(). It now coerces labels to be
	character, and now makes extra room on the plot when the text
	labels are wide.

    o   
	plotMDS() no longer gives an error when the requested number of
	top genes is greater than the total number of rows of data.

    o   
	Code speed-up for alias2SymbolTable()

    o   
	any(duplicated()) replaced by anyDuplicated() in several
	functions.

    o   
	Fix to voom() so that it computes weights correctly even when
	the design matrix is not of full rank.

    o   
	Bug fix for roast() when the fitted model has only one
	coefficient.

                 Changes in version 3.12.0 (2012-03-30)                 

    o   
	read.maimages() with source="agilent" now reads median
	foreground estimates instead of mean foreground. New option
	source= "agilent.mean" preserves earlier meaning of
	source="agilent".

    o   
	Agilent single-channel case study added to User's Guide.

    o   
	removeBatchEffect() now corrects for continuous covariates as
	well as qualitative factors.

    o   
	new function camera() performs competitive gene set tests while
	adjusting for inter-gene correlation.

    o   
	new function interGeneCorrelation() estimates the average
	intergene correlation for a set of genes.

    o   
	columns in output from roast() have been re-ordered.

    o   
	arguments 'selected' and 'selected2' renamed to 'index' and
	'index2' in functions barcodeplot(), geneSetTest() and
	wilcoxGST().

    o   
	default labels for barcodeplot() are now somewhat more
	explicit.

    o   
	new function rankSumTestWithCorrelation extends the
	Wilcoxon-Mann-Whitney test to allow for correlation between
	cases in one of the groups. geneSetTest() now calls this
	function instead of wilcox.test, with a consequence improvement
	in speed.

    o   
	The lfc (log-fold-change) cutoff argument of topTable() is now
	applied to the minimum absolute logFC when ranking by
	F-statistic. Previously lfc was only used when ranking by
	t-statistic.

    o   
	new methods "fast" and "affy" for normalizeCyclicLoess(), with
	"fast" becoming the default method. New argument
	'cyclic.method' for normalizeBetweenArrays() gives access to
	the different cyclic loess methods.

    o   
	There were problems with using the argument gene.weights in
	mroast(). This argument is now permitted to be of the same
	length as the number of probes in the data set. It is then
	automatically subsetted for each gene set.

    o   
	mroast() now uses mid-p-values by default when adjusting for
	multiple testing.

    o   
	neqc(), nec() and normexp.fit.control() now give user-friendly
	error messages when no negative control probes or no regular
	probes are found.

                 Changes in version 3.10.0 (2011-11-01)                 

    o   
	New function voom() allows RNA-Seq experiments to be analysed
	using the standard limma pipeline. An RNA-Seq case study is
	added to User's Guide.

    o   
	treat(), roast() and mroast() can now estimate and work with a
	trend on the prior variance, bringing them into line with
	eBayes().

    o   
	barcodeplot() and barcodeplot2() merged into one function.

    o   
	removeBatchEffect() can now correct for two batch factors.

    o   
	plotMDS is now an S3 generic function. This allows MDS plots to
	be redrawn with new labels without needing to repeat the
	distance or scaling calculations. New S4 class "MDS" to hold
	the multidimensional scaling information output from plotMDS.

    o   
	getEAWP() now gets probe annotation from the expression
	rownames of an EList object, if no other probe annotation is
	available.

    o   
	topRomer() now ranks gene sets by secondary columns as well the
	primary criterion specified, to give a more meaningful ranking
	when the p-values are tied.

    o   
	wilcoxGST() now accepts signed or unsigned test statistics.
	Change to p-value calculation in geneSetTest() when
	rank.only=FALSE to avoid zero p-values and follow
	recommendation of Phipson and Smyth (SAGMB, 2010).

    o   
	plotMA() now recognizes ElistRaw and EList objects
	appropriately.

    o   
	Default span for normalizeCyclicLoess increased from 0.4 to
	0.7. Speed improved when weights=NULL.

    o   
	Weaver case study (Section 11.5) in User's Guide is updated and
	rewritten. Data classes ElistRaw and Elist now described in the
	quick start section of the User's Guide. Other minor updates to
	User's Guide.

    o   
	Bug fix for normalizeBetweenArrays() when object is an EListRaw
	and method="cyclicloess". Previously this function was applying
	cyclicloess to the raw intensities, then logging. Now it logs
	first, then applies cyclicloess.

    o   
	Bug fix to avereps() for EList objects x when x$other is not
	empty.

                 Changes in version 3.8.0 (2011-04-14)                  

    o   
	New method "cyclicloess" for normalizeBetweenArrays().

    o   
	New function normalizeMedianValues(). This is now used by
	normalizeBetweenArrays() for method="scale" when the data
	object is a matrix or EListRaw object.

    o   
	ebayes() and eBayes() now include an option to allow the prior
	variance to be intensity-dependent. Associated with this is a
	new optional argument 'covariate' for fitFDist() and
	squeezeVar().

    o   
	The total degrees of freedom used by ebayes() and eBayes() to
	compute p-values, and therefore also by topTable() and so on,
	is now not allowed to be larger than the total residual degrees
	of freedom pooled over all probes. This limit will normally
	become active only when the prior degrees of freedom is
	estimated to be infinite. Previously the total df was also
	allowed to be infinite in this case, so that p-values were
	computed as if the t-statistics followed a standard normal
	distribution. The change will not affect microarray analyses
	with thousands of genes, but can come into play with simulated
	data or with data sets containing only a few probes. In these
	cases, the ebayes p-values now agree with those from a pooled
	analysis in which the genewise variances are assumed equal.

    o   
	df.total is now included as a component of the MArrayLM object
	output by ebayes() and eBayes().

    o   
	topTable() and toptable() now optionally output confidence
	intervals for the log-fold-changes.

    o   
	neqc() now supports normexp by control background correction
	using negative control values inferred from detection p-values.
	This is mainly applicable to Illumina BeadChips. The default
	value of the 'other.columns' argument of read.ilmn() is changed
	to "Detection".

    o   
	plotSA() now adds the prior variance estimated by eBayes(), if
	available, to the sigma vs A plot.

    o   
	symbols2indices() now returns the indices of all occurrences of
	each symbol on the array, not just the first occurrence. The
	argument names have been changed to be more easily understood,
	and a new argument remove.empty has been added to optionally
	remove gene sets of length zero. Previously this was always
	done.

    o   
	normalizeWithinArrays() no longer checks for printer layout
	information before doing "control" normalization.

    o   
	read.columns() and read.ilmn() now allow column names with
	leading or trailing blanks, although the white space will be
	trimmed.

    o   
	Gene symbol annotation has been added to the Estrogen case
	study in the User's Guide. The Introduction to the User's Guide
	now reflects limma's capabilities for pre-processing data from
	single-channel and Illumina platforms. A reference to Shi et al
	(2010) has been added for neqc(), the installation instructions
	have been updated, and use of the sma package has been removed
	from the code examples.

    o   
	The help pages for nec() and neqc() have been combined into one
	file.

    o   
	Bug fix to squeezeVar(): the output var.posterior was too long
	when there was a non-null covariate and the prior variance was
	estimated to be infinite.

    o   
	Bug fixes to avereps() and avearrays() for matrices, which had
	been treating NA expression values as if they were zero.
	Averages are now computed correctly over the non-missing
	values.

    o   
	Bug fix to mroast(), which had been assigning prior.df
	incorrectly for the second and subsequent gene sets.

    o   
	Fix to gls.series() so that it works correctly even when there
	is only one column of microarray data.

    o   
	Bug fix to plotMDS() when gene.selection="common".

    o   
	Bug fixes to rbind() for EList and EListRaw objects, and to
	subsetting, cbind() and rbind() for EListRaw objects, which
	were not operating correctly on the Eb component.

    o   
	read.ilmn() is now careful to return the gene annotation as a
	data.frame, not a character vector, even when it has only one
	column.

                 Changes in version 3.6.0 (2010-10-18)                  

    o   
	New function avearrays() to average over technical replicate
	arrays.

    o   
	New function normalizeVSN() to apply vsn normalization to limma
	data objects. normalizeBetweenArrays() no longer supports
	method="vsn".

    o   
	New function mroast(), which organizes roast() tests for
	multiple gene sets.

    o   
	New function topRomer() to summarize the output from romer().

    o   
	romer() and romer2() have been consolidated into one function
	romer(). There is a new argument 'set.statistic' to choose the
	set summary statistic, and the old argument 'floor' has been
	removed as no longer needed. romer() no longer outputs p-values
	for the "either" alternative hypothesis; p-values are output
	for "Up", "Down" and "Mixed".

    o   
	New argument 'set.statistic' for roast() to specify which gene
	set summary statistic should be used. The new default is "mean"
	and the original setting is now called "msq". The output from
	roast() no longer includes a column for the "either"
	alternative hypothesis.

    o   
	New S4 class "Roast" for the output from roast().

    o   
	The backgroundCorrect() code has been simplified and a new
	function backgroundCorrect.matrix() introduced for matrix
	arguments. Background intensities are now used correctly when
	the argument RG is an EListRaw object.

    o   
	neqc() now subtracts background intensities Rb if they are
	found in the data object.

    o   
	read.maimages() now supports ImaGene Version 9.0.

    o   
	read.ilmn() now uses readGenericHeader() to skip over header
	information in BeadStudio files, and no longer issues a warning
	if control probe files are not provided.

    o   
	marray is no longer a suggested package.

    o   
	Updates to the 04.Background help page, which gives an overview
	of the background correction functions, and more complete
	documentation for roast() and romer(). Citation details have
	been updated for roast() and propexpr(), and the Pomelo II
	reference has been added to the User's Guide.

    o   
	avereps() for MAList objects was not averaging the "other" data
	matrices correctly. Now fixed.

    o   
	Bug fix to normexp.fit.control() when the argument 'x' is a
	matrix.

    o   
	Bug fixes to roast(), affecting the case when
	set.statistic="msq" and the gene weights change sign, and the
	estimation of the proportion of active genes when there are
	gene weights.

                 Changes in version 3.4.0 (2010-04-23)                  

    o   
	New function normalizeCyclicLoess().

    o   
	read.maimages() has a new argument green.only, which replaces
	the older argument channels. read.maimages() now outputs an
	EListRaw object whenever single channel data is read, and an
	RGList object when two color data is read.

    o   
	read.maimages() now provides the option of reading Agilent
	Feature Extraction data using median foreground summaries.

    o   
	New argument 'robust' for normexp.fit.control() and neqc(),
	giving the option of robust estimation of the background mean
	and standard deviation. Robustness uses the huber() function
	from the MASS package and is judged on the log-scale.
	Computation of the background mean and standard deviation is
	also faster.

    o   
	The default value for the offset in neqc() has been reduced
	from 50 to 16.

    o   
	New argument gene.selection for plotMDS().

    o   
	avedups() and avereps() now have methods for EList objects.

    o   
	New as.data.frame() methods for MAList, EList and EListRaw
	objects.

    o   
	makeContrasts() requires coefficient names (levels) to be
	syntactically valid variable names in R. The intercept column
	name "(Intercept)", which is often produced by the
	model.matrix() function, is now automatically converted, and a
	more detailed diagnostic message is output in the case of
	non-valid names.

    o   
	Speed improvement to avereps(), achieved by calling the base
	package's rowsum() function, following a suggestion of Michael
	Lawrence.

    o   
	MArrayLM objects now re-calculate F-statistics if they are
	subsetted by columns. This ensures that the F-statistics always
	match the contrast columns in the object.

    o   
	The output from treat() now includes a component df.prior.

    o   
	topTreat() now allows genelist to be a vector as well as a
	data.frame. Previously it failed when a vector was input.

    o   
	The truth argument of auROC() can now be logical.

    o   
	Output from vennDiagram() improved to draw complete unbroken
	circles.

    o   
	New "quote" argument for read.ilmn().

    o   
	The raw data for the IlluminaWG-6 case study in the User's
	Guide is now available online, with the URL given in the User's
	Guide. The probe filtering in the Illumina case study has been
	corrected and the results updated.

    o   
	Bug fix to backgroundCorrect() to ensure that normexp.method is
	always correctly passed to normexp.fit(). Previously
	normexp.method was being ignored, in favour of the default,
	when RG was an RGList object.

    o   
	Bug fix to the p-value computation in treat(). This affected
	only p-values greater than 0.5.

    o   
	Bug fix to the row numbers returned by toptable() and
	topTable() when the arguments p or lfc are specified.

    o   
	Bug fix to the sigma calculation in normexp.fit.control().

                 Changes in version 3.2.0 (2009-10-28)                  

    o   
	New functions read.ilmn() and read.ilmn.targets() for reading
	Illumina Whole Genome Expression BeadChip data.

    o   
	New functions normexp.fit.control() and neqc(), which perform
	normexp background correction using negative control
	information. This is especially useful for Illumina BeadChip
	data. neqc() undertakes background correction and quantile
	normalization in one step for EListRaw data objects with
	negative control probes.

    o   
	New function propexpr() for estimating the proportion of
	expressed probes in a microarray, using negative control probe
	information. Especially useful for Illumina BeadChip data.

    o   
	New function genas(), which tests for associations between
	contrasts in a linear model.

    o   
	New function topTreat() for listing the top results from
	treat(). treat() now also outputs thresholded t-statistics.

    o   
	New function alias2SymbolTable() for converting a set of alias
	names to a vector of official gene symbols of the same length.

    o   
	New function wilcoxGST() introduced as a synonym for
	geneSetTest() with ranks.only=TRUE.

    o   
	New function barcodeplot2() for displaying directional gene
	sets with up and down genes shown separately.

    o   
	New options and improved power for romer(). Empirical Bayes
	shrinkage of the residuals is now used to improve statistical
	power, and there are two new options for the set summary
	statistic. The original mean50 statistic is provided in a new
	function romer2(). The new romer() uses an ordinary mean set
	statistic by default, with a floor-mean set statistic as an
	option. Both functions give better statistical power than the
	previous version, and romer() is also computationally quicker.
	romer() now outputs the number of genes in each gene set.

    o   
	Rotation p-values in roast() and romer() are now computed as
	(x+1)/(nrot+1) instead of x/nrot, where x is the number of
	random rotations giving a more extreme statistic than that
	observed.

    o   
	backgroundCorrect() and normalizeWithinArrays() now accept
	EListRaw objects.

    o   
	propexpr() now accepts EListRaw objects, or any other data
	object with an as.matrix method.

    o   
	getEAWP() and lmFit() now return Amean values for EList
	objects.

    o   
	arrayWeights() now displays convergence information when
	TRACE=TRUE for method="genebygene". The convergence criterion
	for arrayWeightsSimple() is now more lenient for large data
	sets, while still achieving about 5 decimal place accuracy, and
	failed convergence from floating point errors is now detected
	and reported with a diagnostic message.

    o   
	strsplit2() now uses ... to pass arguments to strsplit().

    o   
	Speed improvements to avereps(), following suggestions from
	Axel Klenk.

    o   
	read.ilmn() now accepts more variations in the name of the
	ProbeID column.

    o   
	A case study with Illumina BeadChip microarrays has been added
	to the User's Guide. The Oshlack et al (2007) reference on
	normalization of boutique arrays has been added to the
	normalizeWithinArrays help page and to the User's Guide.

    o   
	The sma package has been removed from the list of suggested
	packages.

    o   
	Bug fix to removeBatchEffect(), which gave incorrect results
	when design=NULL.

    o   
	Two fixes to contrasts.fit() when there are non-estimable
	coefficients in the linear model. The function previously gave
	a warning about coercing double to logical, and also failed in
	this situation when the contrast was a single vector instead of
	a matrix.

                 Changes in version 2.18.0 (2009-04-21)                 

    o   
	New class EList for one-channel microarray data and new class
	EListRaw for non-normalized one-channel data. Basic matrix-like
	methods, including cbind, rbind and subsetting, are provided
	for EListRaw objects.

    o   
	New argument 'channels' for read.maimages(), which allows the
	function to read one-channel data.

    o   
	New function plotMDS(), which makes a multidimensional scaling
	plot using a particular distance measure.

    o   
	New function romer() for rotation gene set enrichment analysis.
	This can be viewed as a version of GSEA for linear models.

    o   
	New function symbols2indices(), which matches a list of gene
	sets as symbols against a vector of gene symbols.

    o   
	New function plotSA(), which produces a sigma vs A plot for a
	fitted microarray linear model. The color of the trend line
	drawn by plotSA() has been changed to red.

    o   
	New argument expand.symbols for alias2Symbol(). This can be
	used to prevent aliases from being expanded if they are already
	official symbols.

    o   
	ebayes() now returns lods as a matrix. This ensures that
	MArrayLM objects can always be subsetted by column names, even
	when there is only one column.

    o   
	lmFit() now looks for a design matrix in an MAList data object,
	if one exists. The lmFit() warning message on NA coefficients
	is now more refined, appearing only when the coefficient vector
	is partially NA for some probes.

    o   
	printHead() now prints compactly for recursive lists of
	arbitrary depth.

    o   
	The C code dynamic library is now loaded when the package is
	loaded rather than when it is attached, to enable other
	packages to import limma.

    o   
	The biocViews entry has been changed from Statistics to
	Bioinformatics.

    o   
	Documentation updates for backgroundCorrect(), treat(),
	roast(), geneSetTest(), topTable(), topTableF() and
	alias2Symbol().

    o   
	Bug fixes to the calculation of the up, down, mixed and either
	p-values in romer().

    o   
	Bug fix to toptable(), which caused t-statistics to be out of
	order when p<1 or lfc>0, and another which caused an error when
	p<1 and lfc>0.

    o   
	Bug fixes to the way that topTable() and topTableF() handle
	sort="none".

    o   
	Bug fix to rowname assignment for MAList and RGList objects
	containing matrices in the 'other' component.

    o   
	Fix to gls.series() so that it does not fail when the weight
	matrix contains NA values.

    o   
	Bug fix to printHead() to handle object components which are
	neither atomic nor recursive.

                 Changes in version 2.16.0 (2008-10-22)                 

    o   
	New function roast(), which does rotation gene set testing for
	linear models.

    o   
	New function treat(), which computes empirical Bayes
	moderated-t p-values relative to a minimum required fold-change
	threshold.

    o   
	New function removeBatchEffect(), which removes batch effects
	from microarray data.

    o   
	New function barcodeplot(), which gives a graphical
	representation of geneSetTest() using ranks.

    o   
	New function selectModel(), which implements Akaike Information
	Criterion (AIC) or Bayesian Information Criterion (BIC) model
	selection between alternative linear models. A new method
	"mallowscp" has also been added.

    o   
	New function alias2Symbol() to convert gene aliases to official
	symbols, using the org.Hs.eg.db and similar annotation
	packages.

    o   
	New S3 generic function avereps() for averaging over
	irregularly spaced replicate spots, with a method for MAList
	objects and a default method intended for matrices.

    o   
	New function getDupSpacing(), which determines duplicate
	spacing from a vector of gene IDs. getLayout() with
	guessdups=TRUE can now handle values for ndups greater than 2,
	and getSpacing() recognizes a new value "subarrays", meaning
	that all the probes on an array are repeated in two or more
	subarrays.

    o   
	Substantial tidying up of the normexp.fit() code. The
	optimization step is now done in C, speeding up the computation
	several fold, and the old pure-R normexp.fit() has been
	removed. The old method "neldermead" is now replaced by
	"saddle", and the old methods "bfgs", "nlminb" and "nlminblog"
	are now replaced by "mle". All the user-visible functions
	previously called by normexp.fit() have been removed, including
	dnormexp(), dnormexp.saddle(), normexp.m2loglik() and
	normexp.m2loglik.saddle().

    o   
	backgroundCorrect() has a new argument normexp.method to
	specify the parameter estimation method for normexp background
	correction. The options are "mle", "saddle", "rma" and "rma75".

    o   
	Better treatment of array weights in linear modelling.
	lm.series() and gls.series() now treat array weights as a
	special case when there are no missing values in the expression
	data and no probe-specific weights. This means that the array
	weights are now incorporated into fit$cov.coefficients, so that
	contrasts.fit() correctly takes array weights into account when
	computing the contrast standard errors, which it did not do
	previously. It also means that lmFit() is much faster when
	array weighting is used. There is also a speed improvement to
	gls.series() when there are no missing values and no
	probe-specific weights.

    o   
	New capabilities and arguments for write.fit(). The argument
	'method' allows p-values to be adjusted globally instead of
	separately, and the argument F.adjust allows the F-statistic
	p-values to be adjusted.

    o   
	New arguments sort.by and p.value for topTableF(), making it
	more consistent with topTable(). topTableF() now also allows
	the input argument 'number' to be larger than the number of
	rows of the fitted model object, in which case the requested
	number is set to the number of available rows.

    o   
	New option "none" for the sort argument of topTable().

    o   
	In read.maimages(), support has been added for ArrayVision data
	files with 'Artifact-removed' (ARM) density values.

    o   
	gls.series() now preserves the rownames (probe IDs) of the
	expression object. This affects lmFit() when ndups>1 or block
	is non-NULL, and makes gls.series() consistent with lm.series()
	and mrlm().

    o   
	The following obsolete functions, deprecated in December 2006
	in favour of read.maimages(), have been removed: m.spot,
	a.spot, read.matrix, read.series, rg.series.spot, rg.genepix,
	rg.quantarray and rg.spot.

    o   
	The criterion for the "Active" column output by roast() has
	been changed to be more discriminating.

    o   
	Bug fixes to plotMA(), which was ignoring the array argument
	for RGList objects and was not working for MArrayLM objects.

    o   
	Bug fixes to getEAWP() for PLMset objects, for which the probe
	names, weights and Amean components were not being set
	correctly.

    o   
	Bug fix to removeBatchEffect(), which previously returned an
	error.

                 Changes in version 2.14.0 (2008-04-30)                 

    o   
	New function getEAWP(), introduced to unify the treatment of
	the different classes of microarray data objects that can be
	input to the linear model functions lmFit(), arrayWeights() and
	printtipWeights().

    o   
	Streamlining of the plotMA() code. plotMA() should now work
	correctly for any object class that can be coerced to a matrix,
	for example LumiBatch objects.

    o   
	lmFit() now tries to guess whether a data matrix contains
	log-ratios or log-intensities. When the input data object is a
	matrix, it is not possible to know for certain which is the
	case, and so lmFit() did not previously set the Amean component
	of the output MArrayLM object. lmFit() now sets Amean if the
	input data values are all positive, because the data are almost
	certainly log-intensities in that case.

    o   
	lmFit() now warns if coefficients become inestimable due to
	missing values.

    o   
	All usage of Biobase's exprSet class has been removed or
	replaced with ExpressionSet. The class exprSet2 has been
	removed.

    o   
	normalizeBetweenArrays(method="vsn") has been updated to
	reflect changes in the vsn package, now uses vsnMatrix() when
	the data object is a matrix, and gives an error if the object
	is an MAList. The results are again on the log2 scale, as they
	were before December 2007.

    o   
	The method option "neldermean" for normexp.fit() has been
	corrected to "neldermead".

    o   
	The function rlm.series(), deprecated in 2004, and the
	deprecated function splitName() have been removed.

    o   
	arrayWeights() now gives a nice error message if the number of
	arrays is too few to give statistically useful results.

    o   
	All uses of I() in data.frame() arguments have been removed and
	replaced with stringsAsFactors=FALSE. This ensures that the
	appropriate columns in data.frames have class "character"
	instead of "AsIs".

    o   
	Comments have been added to the geneSetTest() help page to warn
	that the test assumes genewise independence.

    o   
	A section on Multiple Testing Across Contrasts has been added
	to the User's Guide, and the help page for backgroundCorrect()
	has been edited for improved readability.

    o   
	The BibTeX entry returned by citation("limma") now uses
	incollection style instead of inbook, thanks to Joern Toedling.

    o   
	Bug fix to getEAWP(), which was not getting probe names
	correctly from the rownames of the data object when the object
	is a matrix.

    o   
	Bug fix when a matrix data object containing missing values is
	passed to lmFit(). The check for log-intensities vs log-ratios
	did not remove missing values and hence produced an error.

                 Changes in version 2.12.0 (2007-10-08)                 

    o   
	topTable() and toptable() have new arguments p.value and lfc,
	allowing users to cut the gene list on adjusted p-value and
	fold change, rather than just taking a set number of genes as
	before.

    o   
	backgroundCorrect() now accepts a matrix argument.

    o   
	New argument n.pts for normexp.fit(), which becomes the default
	for method="normexp" in backgroundCorrect(). This decreases
	computation time and introduces some robustness. The rule used
	to choose the quantiles has also been improved to give more
	nearly unbiased parameter estimators.

    o   
	Improvements to the numeric computations of dnormexp.saddle(),
	which is used by backgroundCorrect(method="normexp"). New
	function normexp.m2loglik.saddle(), which is the same as
	normexp.m2loglik() but uses the saddle-point approximation.
	normexp.fit() has a new argument 'methods'.

    o   
	New as.matrix() methods for vsn, ExpressionSet and LumiBatch
	objects, so that these objects can be used directly in lmFit().

    o   
	decideTests(method="hierarchical") now passes adjust.method
	down to the second (t-test) level of testing. Previously the
	second level testing was always "holm". The spelling has also
	been corrected from "heirarchical" to "hierarchical".

    o   
	contrasts.fit() now warns if the row names of the contrast
	matrix do not match the column names of the coefficients.

    o   
	plotMA3by2() has a new argument 'device' to specify the graphic
	format.

    o   
	The plot character and size can now be passed to volcanoplot()
	as arguments.

    o   
	The Ritchie et al (2007) reference has been added to the User's
	Guide and to the backgroundCorrect and normexp help pages, and
	loessfit.Rd has been edited to better acknowledge the lowess
	and loess authors.

    o   
	Correction to loessFit() because the lowess() function is now
	in stats instead of base.

    o   
	Bug fix to read.columns() to stop a spurious warning message
	when text.to.search has length greater than one.

    o   
	Bug fix for as.matrix.vsn(), which allows vsn objects from
	vsn2() to be used directly in lmFit().

                 Changes in version 2.10.0 (2007-04-26)                 

    o   
	A NAMESPACE has been introduced to the package. The functions
	matvec() and vecmat() have been renamed to .matvec() and
	.vecmat() and are no longer exported. All objects with names
	not starting with "." are exported.

    o   
	Changes to the column headings from topTable(). 'M' is now
	'logFC' and 'A' is now 'AveExpr'.

    o   
	lmFit() now supports ExpressionSet objects, and there is a new
	function as.matrix.ExpressionSet().

    o   
	New function strsplit2(), which replaces splitName().
	splitName() is deprecated.

    o   
	New function read.columns(), which is similar to read.delim()
	but reads specified columns only. read.columns() replaces the
	functions getColClasses() and namesInFun().

    o   
	New function mergeScansRG().

    o   
	New argument 'other.columns' for read.imagene().

    o   
	The old functions designed to read image data files into
	data.frames are now deprecated. This affects read.matrix,
	rg.series.spot, read.series, m.spot, a.spot, rg.spot,
	rg.quantarray and rg.genepix.

    o   
	wtVariables() has been renamed to namesInFun().

    o   
	normalizeRobustSpline() now works even when there is only one
	print-tip group, although it is designed to handle multiple
	print-tip groups.

    o   
	The function .onAttach() replaces the old .First.lib().

    o   
	normalizeForPrintorder(plot=TRUE) now produces no output, to
	agree with the documentation.

    o   
	The default number of digits in write.fit() has been changed to
	3.

    o   
	The User's Guide sections on spot quality weights and quality
	assessment have been expanded, a section on array quality
	weights has been added, and the case studies have been updated
	for the current version of limma.

    o   
	Bug fix to read.maimages() for source="arrayvision".
	read.images() now reads ArrayVision files again, which it has
	not done since version limma 2.3.1.

    o   
	Bug fixes to read.maimages() for source="quantarray", which was
	reading too few lines when searching for "Begin Data" in the
	second and following files and was not setting the annotation
	columns, and for the Agilent and generic sources.

    o   
	Bug fix to read.columns(), to read SPOT files with a leading
	column of row numbers.

    o   
	Bug fix to topTable(). The values sort="M" and resort.by="M"
	needed to be updated to sort="logFC" and resort.by="logFC", and
	the values sort="AveExpr" and resort.by="AveExpr" are now
	allowed.

    o   
	Bug fix to lmFit(), which was giving an error with marrayNorm
	objects because of incorrect setting of Amean.

    o   
	Bug fix to write.fit(), which was writing ambiguous column
	names for the coefficients, t-statistics and p-values when the
	MArrayLM object had only one column.

    o   
	Bug fix to lm.series() and gls.series(), which were returning
	errors when the design matrix was not of full rank and the
	columns were named.

    o   
	volcanoplot() now allows a NULL value for the 'names' argument.

                 Changes in version 2.8.0 (2006-10-04)                  

    o   
	New function topTableF() to rank genes on the basis of
	F-statistics. topTable() now accepts a vector argument coef and
	calls topTableF() to produce a ranking by F-statistic if
	length(coef)>1. topTable() with coef=NULL ranks genes by the
	F-statistic for all the contrasts.

    o   
	New argument 'coefficients' for contrasts.fit(). This provides
	a simple way to specify the contrast matrix when the contrasts
	are just a subset of the original coefficients.

    o   
	New argument 'contrasts' for makeContrasts(), which accepts a
	character vector of contrasts. The matrix produced by
	makeContrasts() now has named dimensions.

    o   
	New argument 'lfc' for decideTests() to require a minimum
	fold-change.

    o   
	normalizeWithinArrays() now uses asMatrixWeights() to process
	the weights argument, so that the weights can be a vector of
	probe weights, a vector of array weights, or a matrix of spot
	weights. The weights argument of modifyWeights() now has a
	default value.

    o   
	New function exprs.MA() to extract the log-expression matrix
	from an MAList object.

    o   
	New function plotlines().

    o   
	New function plotFG() for foreground-background plots.

    o   
	New function as.matrix.PLMset(), which allows lmFit() to work
	correctly on PLMset objects.

    o   
	New arguments for vennDiagram() to allow colors and the
	printing of multiple sets of counts on the same diagram.

    o   
	wtflags() has a new argument cutoff, and the argument w has
	been renamed to weight.

    o   
	In geneSetTest(), the values "two.sided", "less" and "greater"
	are now permitted as synonyms for "either", "down" and "up".
	geneSetTest() no longer issues a warning with type="t" and all
	positive values for the statistic.

    o   
	read.imagene() now uses mean background instead of median if
	the auto segmentation method has been set, and
	readImaGeneHeader() now allows for extraneous trailing white
	space in the lines of the data files.

    o   
	In read.maimages(), flush=TRUE has been added to all instances
	of read.table(). This makes read.maimages() tolerant of
	spurious columns added to the end of data lines.

    o   
	Improvements to lm.series(), gls.series() and rlm.series() to
	better preserve column names.

    o   
	Improvement to normalizeQuantiles() to reduce memory
	requirements.

    o   
	decideTests() now preserves probe row names.

    o   
	Subsetting for MArrayLM objects has been revised so that the
	contrast matrix is subsetted rather than the design matrix.

    o   
	makeContrasts() now gives an informative error message if the
	parameter names are not syntactically valid.

    o   
	The previously deprecated function array2channel() has been
	removed.

    o   
	A new section on Fitted Model Objects has been added to the
	User's Guide, together with a table of image analysis programs,
	an updated Bob case study, and the CARMAweb reference. The
	warning that lmscFit() is "experimental" has been removed.

    o   
	normalizeWithinArrays() was incorrect with method="composite"
	and weights=NULL. Now fixed.

    o   
	Bug fixes to kooperberg(), plotlines(), plotMA3by2() and to
	read.imagene(), which was trying to read too many data rows
	when there were multiple ImaGene fields.

    o   
	Fix to read.maimages(): using readGenericHeader() to get column
	names was not working when sep or quote were different from the
	defaults.

                 Changes in version 2.6.0 (2006-04-27)                  

    o   
	New function arrayWeightsSimple(), with a new argument
	'maxratio' which stops the iteration when the ratio of largest
	to smallest weights becomes large. arrayWeights() now returns a
	vector instead of a matrix, and is faster and more accurate.

    o   
	New function asMatrixWeights(), which is used by all the linear
	model functions so that they can accept vectors of probe or
	array weights in place of a full matrix of weights.

    o   
	New generic function avedups(), with default and MAList
	methods.

    o   
	New function plotFB().

    o   
	New option "rma" for the method argument of
	backgroundCorrect().

    o   
	All the normexp functions now use simpler arguments: 'x'
	instead of 'foreground' and 'background', and a vector argument
	'par' instead of separate arguments for each parameter.
	normexp.fit() now uses a saddlepoint approximation to the
	normexp density and reverts to the Nelder-Mead optimisation
	method, giving numerically reliable computations. New functions
	dnormexp() and dnormexp.saddle().

    o   
	fitFDist() now treats very small and zero variances in a
	unified way, and the bounding of standard deviations away from
	zero now uses a smaller bound. This slightly changes the
	hyperparameter estimates and significance results produced by
	eBayes().

    o   
	topTable() now includes separate columns for raw and adjusted
	p-values.

    o   
	New S3 methods fitted() and residuals() for the MArrayLM class,
	and new S3 methods for 'dimnames<-' for RGList and MAList
	objects.

    o   
	Subsetting of RGList, MAList and MArrayLM objects by rownames
	now works correctly even if not all components have rownames.
	When an MArrayLM object is subsetted, the targets frame is no
	longer subsetted and the design matrix subsets only on columns.

    o   
	duplicateCorrelation() and intraspotCorrelation() now return
	atanh-correlations, and the corresponding output components
	have been renamed to 'atanh.correlations'.

    o   
	The correlation argument of lmFit() no longer has a default
	value.

    o   
	Support for ScanArray Express has been added to
	read.maimages(), and read.maimages() now reads BlueFuse v3.2
	files correctly. The files argument of read.maimages() can now
	be a data.frame, assumed to be the targets frame.
	read.maimages() now uses check.names=FALSE to preserve
	annotation column names as input, uses the X position column to
	determine printer layout information for source="genepix", and
	no longer tries to guess ndups for GenePix data, which was
	found to be unreliable for small boutique arrays.

    o   
	readGenericHeader() replaces readBlueFuseHeader() and is now
	used by read.maimages() to get the skip value and column names
	for generic source files. readGenericHeader() now uses
	protectMetachar() so that special characters can be used in
	column headings.

    o   
	Changes to the argument list and defaults for geneSetTest() to
	make it more intuitive.

    o   
	decideTests() now supports adjust.method="BY".

    o   
	normalizeMedianDeviations() and normalizeMedians() have been
	replaced by normalizeMedianAbsValues(), which is resistant to
	floating underflow. The default method for
	normalizeBetweenArrays() has been changed to "Aquantile".

    o   
	The deprecated functions dupcor.series() and kooperberg_old()
	have been removed.

    o   
	readTargets() now checks that the labels are unique before
	making row.names.

    o   
	MAList subsetting now supports the 'other' component, and
	cbind() and rbind() now support the 'other' component in RGList
	and MAList objects.

    o   
	limma now formally depends on R version 2.2.0 or higher.

    o   
	A section on Paired Samples has been added to the User's Guide
	and the help page for normalizeWithinArrays() has been edited
	and expanded. The help pages for lm.series(), gls.series() and
	mrlm() now make clear that they are utility functions called by
	lmFit(), and the help page for topTable() better explains the
	differences between toptable() and topTable(). The definition
	of interaction in the Weaver case study has been corrected.

    o   
	Bug fix to decideTests(), which failed with method="nestedF"
	and adjust.method="BH".

    o   
	Bug fix to ensure that makeContrasts() works correctly when the
	level names happen to be the same as local variable names.

    o   
	Bug fixes to merge.RGList() and merge.MAList(), which used to
	break when there were any components of the data objects other
	than intensity matrices.

    o   
	Bug fixes to topTable() when some p-values are missing and to
	as.data.frame.MArrayLM() when the row subset is of length 1.

    o   
	Bug fixes to read.maimages() for source="genepix" when there
	was only one block of spots, for source="imagene" when a
	data.frame of file names was confused with a targets file, and
	for source="genepix" when the meta-grid layout could not be
	determined.

    o   
	kooperberg() now gives an informative error message if the
	input is not an RGList.

                 Changes in version 2.2.0 (2005-10-13)                  

    o   
	kooperberg() now accepts an RGList object instead of requiring
	each gpr file to be read into a separate data.frame. The old
	function has been renamed kooperberg_old().

    o   
	Extensive clean-up of the background correction functions based
	on the normexp distribution. fit.normexp0() and
	m2loglik.normexp() have been removed and the functions are now
	called normexp.fit(), normexp.m2loglik(), normexp.grad() and
	normexp.signal().

    o   
	The deprecated functions designMatrix() and classifyTests()
	have been removed.

    o   
	makeContrasts() now accepts expression- or character-valued
	variable arguments.

    o   
	"fdr" has been changed to "BH" throughout as the p.adjust()
	method, and the default adjust.method for topTable() has been
	changed to "BH".

    o   
	New options source="genepix.custom" and source="genepix.median"
	for read.maimages(). The default value for the source argument
	is now NULL. The columns argument can now be arbitrary,
	provided that the two foreground channels are included, and the
	inclusion of background columns is now optional.

    o   
	Support for BlueFuse files has been added to read.maimages(),
	with a new function readBlueFuseHeader().

    o   
	readImaGeneHeader() has been entirely re-written and now
	supports ImaGene 6.0 and multiple sub-array fields.

    o   
	New method "control" for normalizeWithinArrays().

    o   
	normalizeWithinArrays(method="median") now uses a weighted
	median where appropriate, and there is a new function
	weighted.median(). normalizeWithinArrays() now checks whether M
	or A are vectors, and gives an informative error for
	method="printtiploess" if the layout is incompatible with the
	data dimensions.

    o   
	arrayWeights() now includes a full "reml" option, and works
	correctly on the chip level coefficients for PLMset objects.

    o   
	eBayes() now returns the F.p.value component as a vector rather
	than a matrix.

    o   
	Point size 20 and a new path argument have been added to
	imageplot3by2().

    o   
	New introductory chapters 04.Background and 08.Tests for the
	online help system, together with a general cleaning up of the
	chapter system.

    o   
	convest() now checks that the input p-values are between 0 and
	1.

    o   
	Changes to write.fit() to make it tolerant of not finding
	expected components such as Amean in the fit object.

    o   
	The User's Guide has been converted to LaTeX report style, with
	new sections on getting help and on citing limma, an updated
	Weaver case study, and the dendritic cell direct comparison
	example now using modelMatrix(). A note has been added to the
	duplicateCorrelation() help page about the minimum number of
	arrays needed for the function to return statistically useful
	results.

    o   
	Bug fix to plotDensities(), where the background was being
	subtracted twice.

    o   
	Work-around in eBayes() for the pf(q,df1,df2=Inf) bug in R
	2.1.0.

    o   
	Bug fix to normexp.signal() to allow NAs in the signal.

    o   
	Bug fix to RGList subsetting, where the targets component was
	subsetted incorrectly with j but missing i.

    o   
	Bug fix to as.data.frame.MArrayLM() when the fit contains only
	one contrast and there are matrices stored as vectors.

    o   
	modelMatrix() now gives a helpful error message if 'targets' is
	missing.

                 Changes in version 1.9.6 (2005-05-18)                  

    o   
	New function arrayWeights(), contributed by Matt Ritchie, which
	estimates relative quality weights for each array in a
	multi-array experiment. The previous version of the function
	has been renamed arrayWeightsQuick().

    o   
	New function convest() to estimate the proportion of true null
	hypotheses from a vector of p-values.

    o   
	New function volcanoplot().

    o   
	New as.matrix() methods for all the limma data classes, and a
	new as.data.frame() method for MArrayLM objects.

    o   
	New BFGS version of fit.normexp(), contributed by Jeremy
	Silver, with several new utility functions to compute the
	likelihood and gradient. The old Nelder-Mead version has been
	renamed fit.normexp0(). signal.normexp() is now more resistant
	to floating overflow and underflow, and fit.normexp() now
	catches and reports optimization errors.

    o   
	lm.series() and lmFit() now treat a linear model with no
	weights and no missing values as a special case, giving a great
	increase in speed for typical Affymetrix analyses.

    o   
	decideTests() now allows for NA p-values for method="separate"
	or "global", where it was previously giving wrong answers, and
	summary.TestResults() also allows for NA p-values.
	decideTests() now runs eBayes() if the MArrayLM object is found
	not to contain t-statistics.

    o   
	The log and unlog arguments have been removed from MA.RG() and
	RG.MA(). RGList objects are now always assumed to contain
	unlogged intensities. There are corresponding changes to
	plotDensities(), for which log.transform=TRUE is now the
	default, and RG.MA() has a new argument unlog.

    o   
	limma now officially requires R version 2.0 or higher.

    o   
	limmaUsersGuide() replaces limmaguideURL() and now outputs the
	file name rather than a URL. The html version of the User's
	Guide has been removed.

    o   
	The default column name for gene names in topTable() output is
	now 'ProbeID', and lmFit() now captures rownames if the data
	object is a matrix.

    o   
	readTargets() has a new '...' argument and now looks for
	columns "Label" or "FileName" to make row.names if the
	row.names argument is NULL. removeExt() now coerces its
	argument to character.

    o   
	duplicateCorrelation() now traps the error condition when all
	the non-missing observations for a gene belong to the same
	block.

    o   
	readImaGeneHeader() now allows for headers up to 100 lines,
	previously 60.

    o   
	The 'columns' argument no longer overwrites the 'source'
	argument of read.maimages().

    o   
	New sections in the User's Guide on Time Course Experiments,
	Separate Channel Analyses, Several Groups, Adjusting for
	Multiple Testing, and software packages using limma. The User's
	Guide now uses BibTeX for its reference list. The CITATION file
	has been updated to the Bioconductor book chapter.

    o   
	Bug fixes to lmFit() when there are no weights or missing
	values and the residual degrees of freedom are 0 or 1, and when
	there are non-estimable coefficients.

    o   
	Bug fix to uniquegenelist(), which now preserves the data.frame
	or matrix class. This fixes a bug when fitting a model to an
	exprSet object with duplicate probes.

    o   
	Bug fix to normalizeRobustSpline() when Sigma0 is zero, that
	is, when the method reduces to a global spline.

    o   
	Bug fix to normalizeBetweenArrays() with method="Gquantile" or
	"Rquantile", which now changes only the A-values.

    o   
	Bug fix to plotDensities() when the object is an MAList and
	log.transform=TRUE, which should give a log rather than a
	log-log scale.

    o   
	Bug fix so that lmFit() calls mrlm() rather than the deprecated
	rlm.series().

    o   
	Bug fixes to changeLog(), to getLayout2() when the GAL file has
	no header, to readGAL() for the stricter regular expression
	syntax of R 2.1.0, and to subsetting of MArrayLM objects when
	the components are vectors rather than matrices.

    o   
	intraspotCorrelation() now uses try() to tolerate some fit
	errors from remlscore().

                 Changes in version 1.8.5 (2004-10-25)                  

    o   
	All the linear modelling functions now return the covariance
	matrix of the estimated coefficients. This improves support for
	models with covariance structures, such as random effects
	models for technical replicates, mixed models for log-intensity
	analysis of two color data, and duplicate spots.
	contrasts.fit() and classifyTestsF() now use the covariance
	matrix stored in the data object.

    o   
	New function decideTests() for global multiple testing across
	probes and contrasts.

    o   
	New function geneSetTest().

    o   
	New function nonEstimable(). lmFit() now reports non-estimable
	coefficients, and contrasts.fit() stops with an error message
	if an attempt is made to take a contrast of a non-estimable
	parameter.

    o   
	New background correction method "normexp" for
	backgroundCorrect(), together with associated functions.
	backgroundCorrect() also has a new argument 'offset', and
	MA.RG() and normalizeWithinArrays() now accept arguments
	'bc.method' and 'offset'.

    o   
	New functions imageplot3by2() and plotMA3by2() to write plots
	to files. imageplot() now shows a z-range legend, has a new
	argument 'mar', and traps infinite z values with an informative
	error message.

    o   
	plotMA() now does single-channel MA-plots and accepts exprSet,
	matrix and MArrayLM objects. Points with zero weight are no
	longer plotted by default.

    o   
	eBayes() now returns F-statistics and the corresponding
	p-values, and checks that the design matrix is of full rank
	before computing the F-statistic.

    o   
	New summary methods for RGList, MAList and MArrayLM objects,
	and a slicker summary method for TestResults objects.

    o   
	New argument other.columns for read.maimages(). Subsetting of
	RGList objects and MA.RG() now accommodate an 'other'
	component.

    o   
	read.maimages() now handles the new format SMD files, tries to
	set the printer layout for Agilent data, and calls
	readGPRHeader() to get the skip records for each gpr file. New
	functions readSMDHeader() and getLayout2(), the latter reading
	GAL file headers.

    o   
	New utility functions protectMetachar(), trimWhiteSpace() and
	tZscore().

    o   
	New function changeLog() to display the limma change log, which
	has been moved to the inst/doc directory of the package.

    o   
	lmFit() now accepts PLMset objects and better recognises when a
	marrayNorm object has a non-empty list of gene names.

    o   
	rlm.series() is deprecated in favour of mrlm().

    o   
	kooperberg() now returns an RGList.

    o   
	heatDiagram() now chooses the color range more carefully, so
	that red is associated only with positive fold changes and
	green with negative, separates the primary up and down genes
	with white space, and has a new argument 'mar'.

    o   
	The install.R file has been removed and replaced with LazyLoad
	in the DESCRIPTION file. limma now passes R CMD check under R
	2.0 and was for the first time posted to CRAN as well as to
	Bioconductor.

    o   
	anova.MAList() now checks whether the design matrix has more
	than one column, and write.fit() now works on MArrayLM objects
	when eBayes() has not been used.

    o   
	New sections in the User's Guide on Installation and on Special
	Designs, the Estrogen case study redone, and many edits
	throughout. A citation entry has been added for limma. The
	Swirl and ApoAI case studies have also been updated.

    o   
	Bug fixes to contrasts.fit() when there are non-estimable
	coefficients, to decideTests() for method="hierarchical" and
	method="nestedF", to kooperberg() when the background is zero,
	and to read.imagene().

    o   
	Bug fixes to read.maimages() for Agilent data, to
	readTargets(), and to dim() for RGList, MAList and MArrayLM
	objects, which was returning NULL when there was just one
	column.

    o   
	Bug fix to vennCounts() when there are no significant results
	for one or more contrasts.

    o   
	normalizeWithinArrays(method="composite") now allows for NAs,
	and calls to rlm() in normalizeRobustSpline() now explicitly
	set prior weights.

                 Changes in version 1.6.6 (2004-05-17)                  

    o   
	New functions lmscFit() and intraspotCorrelation() for separate
	channel analysis of two color data, together with a new
	documentation entry on single channel analysis. lmscFit() was
	originally introduced as lmsc.series() and now produces an
	MArrayLM object.

    o   
	New function write.fit() for outputting the results of a linear
	model fit.

    o   
	New function modelMatrix() to construct design matrices for
	microarray experiments with common references. modelMatrix()
	replaces designMatrix(), which is deprecated. The use of 'ref'
	is now more general and does not have to occur on every array.

    o   
	New function array2channel() to convert targets files from a
	by-array to a by-channel representation.

    o   
	New function auROC() to compute the exact area under the ROC
	curve.

    o   
	New function poolVar() for Welch-style pooling of sample
	variances with unequal variances.

    o   
	New function squeezeVar(), originally introduced as
	smoothVar().

    o   
	New function FStat(). classifyTests() has been renamed to
	classifyTestsF(), and classifyTestsP() now extracts the degrees
	of freedom from the data object.

    o   
	The S3 class "classification" has been replaced by the S4 class
	"TestResults", including show and summary methods.
	classifyTestsF(), classifyTestsT() and classifyTestsP() now
	produce TestResults objects.

    o   
	duplicateCorrelation() now uses randomizedBlockFit() from the
	statmod package instead of gls() from the nlme package. This
	results in a several-fold increase in speed for
	duplicateCorrelation() and dupcor.series(). dupcor.series() is
	now deprecated and limma depends on statmod.

    o   
	New argument 'block' for duplicateCorrelation(), gls.series()
	and lmFit() to treat technical replicates as randomized blocks.

    o   
	New methods Rquantile, Gquantile and Tquantile for
	normalizeBetweenArrays(), and a new method "vsn".

    o   
	New function getSpacing(), and getLayout() now has an option to
	guess the spacing between duplicate spots. New function
	blockDiag() to form block diagonal matrices. printorder() has
	been upgraded to accommodate spacing by rows or topbottom.

    o   
	New function modifyWeights().

    o   
	New argument 'resort.by' for toptable() and topTable().

    o   
	New arguments 'mar' and 'cex' for vennDiagram(), which reduce
	white-space and control text size.

    o   
	New argument 'annotation' for read.maimages(), and
	source="agilent" added to read.maimages().

    o   
	readGAL() now sorts GAL files into standard order if they are
	not already sorted, and read.maimages() now sets the gene list
	directly from the gpr files, so readGAL() will usually no
	longer be required.

    o   
	New merge method for MAList objects, and new rbind methods for
	RGList and MAList objects.

    o   
	lmFit() now extracts probe IDs from exprSet objects.

    o   
	vennCounts() now uses table() for the major computation and is
	therefore much faster.

    o   
	backgroundCorrect(method="edwards") now handles NAs.

    o   
	A Sweave-style vignette has been added, as well as the User's
	Guide, and new functions usersguideURL() and .First.lib()
	implement a limma entry in the Windows drop-down Vignettes
	menu.

    o   
	Estrogen and Ecoli-lrp case studies have been added to the
	User's Guide, and internal links have been added to the
	contents section.

    o   
	Substantial upgrade to the functions which identify and track
	control spots from the gene list, including readTargets(),
	readSpotTypes(), controlStatus() and plotMA(). New 'path' and
	'...' arguments for readSpotTypes() and readTargets().

    o   
	Bug fixes to designMatrix(), which was giving the wrong matrix
	when the common reference was Cy5 for the first array, and to
	printorder() with spacing="topbottom", which was returning
	vectors of the wrong length.

    o   
	Bug fixes to imageplot() and heatdiagram(), which caused
	over-printing when using par(mfrow).

    o   
	Bug fix to normalizeRobustSpline() to prevent an error when the
	spline basis becomes singular.

    o   
	Changes to loessFit() to avoid errors with small numbers of
	observations.

    o   
	Bug fix to duplicateCorrelation(), which was not finding the M
	matrix when the object was not an MArrayLM, and a check has
	been added for correlations less than -1.

    o   
	Bug fixes to write.fit(), which was failing when adjusting
	p-values with multiple contrasts, and further fixes to
	accommodate the TestResults class.

    o   
	Refinements to the estimation of var.prior in ebayes() and
	related functions.

    o   
	Bug fix to gls.series() to ensure that the spacing and weights
	arguments are passed to duplicateCorrelation().

    o   
	Bug fixes to backgroundCorrect(method="edwards") and to
	plotPrintTipLoess().

                 Changes in version 1.2.8 (2003-10-30)                  

    o   
	New function lmFit(), an object-orientated interface to linear
	modelling which accepts RGList, MAList, marrayNorm and exprSet
	objects. New MArrayLM class to hold the fitted model, and a new
	virtual class LargeDataObject with an associated show method.

    o   
	Object-orientated versions of several functions are being
	gradually introduced: eBayes() for ebayes(), topTable() for
	toptable() and heatDiagram() for heatdiagram().

    o   
	New function makeContrasts() to construct contrast matrices.

    o   
	New function duplicateCorrelation() as an object-orientated
	wrapper for dupcor.series().

    o   
	New function designMatrix() to construct design matrices for
	microarray experiments with common references.

    o   
	New functions vennCounts() and vennDiagram() for Venn diagram
	plots, with a new argument 'include'.

    o   
	New function loessFit(), giving substantial speed improvements
	for loess normalization. loessFit() has a new argument 'bin'
	and the interpolation settings have been fine tuned.

    o   
	New functions for Kooperberg Bayesian background correction,
	with the internal functions now hidden from the user.

    o   
	New function plotDensities(), contributed by Natalie Thorne.

    o   
	New backgroundCorrect() methods "half", "minimum", "movingmin",
	"edwards" and "none".

    o   
	read.maimages() now supports ImaGene, ArrayVision and SMD data
	files, and reading of QuantArray files has been fixed. New
	functions readGPRHeaders() and readImageneHeaders(), and
	read.imagene() now allows for changes of header information
	between arrays.

    o   
	classifyTests() now supports MArrayLM objects, accepts design
	and contrast matrices, and returns an F-statistic.

    o   
	New class exprSet2, and new function topTable().

    o   
	Support for correlated design matrices has been added to
	contrasts.fit().

    o   
	New cbind, rbind and subsetting methods for RGList and MAList
	objects, and support for much extra structure in these objects.

    o   
	New argument 'ties' for normalizeBetweenArrays() and new
	argument 'mar' for imageplot().

    o   
	normalizeWithinArrays(), normalizeForPrintorder() and
	plotPrintorder() are no longer generic, which simplifies the
	documentation. The documentation for normalizeBetweenArrays()
	has also been consolidated.

    o   
	New section in the User's Guide on single channel
	normalization, contributed by Natalie Thorne, expanded sections
	on reading data, and a new affy example.

    o   
	Bug fixes to classifyTests(), to loessFit(), to toptable(),
	which was displaying incorrect A-values, to wtIgnore.Filter()
	with GenePix data, and to backgroundCorrect() with
	method="minimum".

                 Changes in version 1.0.8 (2003-05-29)                  

    o   
	limma was included in the Bioconductor project for the first
	time, as part of Bioconductor release 1.2.

    o   
	The package was originally called smawehi and was made public
	for the first time on 11 November 2002. It was renamed limma,
	with the title "Linear Models for Microarray Data", in April
	2003. The early versions of the package were intended to be
	used in conjunction with the sma package from the University of
	California at Berkeley.

    o   
	New S4 classes RGList and MAList for two color microarray data,
	including setValidity() methods. Previously the data objects
	had the same structure but were unclassed.

    o   
	New function MA.RG() to make MAList objects from RGList objects
	or lists, and a new merge() method for RGList objects.

    o   
	New function backgroundCorrect().

    o   
	New S4 generic functions normalizeWithinArrays() and
	normalizeBetweenArrays(), together with normalizeMedians(),
	normalizeQuantiles(), normalizeMedianDeviations() and
	normalizeForPrintorder(). Several of these functions were
	renamed from earlier versions: normalize.quantile() to
	normalizeQuantiles(), norm.scale.ma() to
	normalizeMedianDeviations() and normalize.printorder() to
	normalizeForPrintorder().

    o   
	New function normalizeRobustSpline(), with a corresponding
	option for normalizeWithinArrays(), which implements print-tip
	normalization by fitting spline curves robustly to each
	print-tip group and then applying empirical Bayes moderation
	across the array.

    o   
	New functions wtarea() and wtflags() to make quality weights
	for microarray data from image analysis statistics, and a new
	function wtIgnore.Filter() for QuantArray data.

    o   
	New functions classifyTests() and classifyTests.vector() for
	multiple testing across genes and more than one contrast.

    o   
	New function plotMA() to make MA plots for both two color and
	single-channel data, and a new function plotPrintTipLoess() to
	display lowess normalization curves for printed two color
	microarrays. plotPrintorder() was renamed from
	plot.printorder().

    o   
	Other functions renamed at this time include anova.series() to
	anova.MAList(), fdist.fit() to fitFDist() and
	trigamma.inverse() to trigammaInverse().

    o   
	New utility functions isNumeric() and helpMethods().

    o   
	A printable pdf version of the User's Guide is now provided.

    o   
	Bug fixes to ebayes() when there are more than two
	coefficients, to read.maimages() for QuantArray data, and to
	classifyTests().

                  Changes in version 0.3 (2002-11-25)                   

    o   
	The limma package was originally called the smawehi package,
	because it was intended to be used in conjunction with the sma
	package from the University of California at Berkeley, and was
	made public via the repository
	http://bioinf.wehi.edu.au/smawehi. The package originally
	focused on the analysis of two-color microarrays.
	
	Version 0.3 of the package formed the basis of the One Day
	Course "Statistics for Microarray Data Analysis" presented at
	the Australian Genstat Conference in Perth, Australia, on 2
	December 2002 by Terry Speed, Gordon Smyth and Natalie Thorne.

    o   
	The package contained the following functions: a.spot,
	anova.series, bwss, bwss.matrix, contrasts.fit, dl2norm,
	dnorml2norm, dupcor.series, ebayes, fdist.fit, gls.series,
	gridc, gridr, heatdiagram, image.array, lm.series, m.spot,
	matvec, norm.scale.ma, normalize.printorder,
	normalize.quantile, plot.printorder, qqt, read.series,
	rg.genepix, rg.quantarray, rg.series.spot, rg.spot, rlm.series,
	spotc, spotr, txmixture.matrix, txmixture.vector, toptable,
	trigamma.inverse, uniquegenelist, unwrapdups, vecmat.