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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("FourCSeq")
In most cases, you don't need to download the package archive at all.
FourCSeq
Package analyse 4C sequencing data
Bioconductor version: 3.0
FourCSeq is an R package dedicated to the analysis of (multiplexed) 4C sequencing data. The package provides a pipeline to detect specific interactions between DNA elements and identify differential interactions between conditions. The statistical analysis in R starts with individual bam files for each sample as inputs. To obtain these files, the package contains a python script (extdata/python/demultiplex.py) to demultiplex libraries and trim off primer sequences. With a standard alignment software the required bam files can be then be generated.
Author: Felix A. Klein, EMBL Heidelberg
Maintainer: Felix A. Klein <felix.klein at embl.de>
Citation (from within R,
enter citation("FourCSeq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("FourCSeq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("FourCSeq")
| R Script | FourCSeq | |
| Reference Manual |
Details
| biocViews | Preprocessing, Sequencing, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL (>= 3) |
| Depends | R (>= 3.0), GenomicRanges, ggplot2, DESeq2, splines, methods |
| Imports | DESeq2, Biobase, Biostrings, GenomicRanges, Rsamtools, ggbio, reshape2, rtracklayer, fda, GenomicAlignments, gtools, Matrix |
| LinkingTo | |
| Suggests | BiocStyle, knitr, TxDb.Dmelanogaster.UCSC.dm3.ensGene |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | FourCSeq_1.0.0.tar.gz |
| Windows Binary | FourCSeq_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | FourCSeq_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | FourCSeq_1.0.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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