Package: autonomics
Type: Package
Title: Unified Statistical Modeling of Omics Data
Version: 1.14.7
Authors@R: c(person("Aditya",   "Bhagwat",    email = "aditya.bhagwat@uni-marburg.de",    role = c("aut", "cre")), 
             person("Richard",  "Cotton",     email = "richierocks@gmail.com",            role = "ctb"),
             person("Shahina",  "Hayat",      email = "shahina.hayat@hotmail.com",        role = "ctb"),
             person("Laure",    "Cougnaud",   email = "laure.cougnaud@openanalytics.eu",  role = "ctb"),
             person("Witold",   "Szymanski",  email = "witold.szymanski@uni-marburg.de",  role = "ctb"),
             person("Vanessa",  "Beutgen",    email = "vanessa.beutgen@uni-marburg.de",   role = "ctb"),
             person("Willem",   "Ligtenberg", email = "wligtenberg@gmail.com",            role = "ctb"),
             person("Hinrich",  "Goehlmann",  email = "hinrich@goehlmann.info",           role = "ctb"),
             person("Karsten",  "Suhre",      email = "kas2049@qatar-med.cornell.edu",    role = "ctb"),
             person("Johannes", "Graumann",   email = "johannes.graumann@uni-marburg.de", role = c('aut', 'sad')))
Description: 
  This package unifies access to Statistal Modeling of Omics Data.
  Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon).
  Across coding systems (treatment, difference, deviation, etc).
  Across model formulae (with/without intercept, random effect, interaction or nesting).
  Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics).
  Across projection methods (pca, pls, sma, lda, spls, opls).
  Across clustering methods (hclust, pam, cmeans).
  It provides a fast enrichment analysis implementation.
  And an intuitive contrastogram visualisation to summarize contrast effects in complex designs.
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
biocViews: Software, DataImport, Preprocessing, DimensionReduction,
        PrincipalComponent, Regression, DifferentialExpression,
        GeneSetEnrichment, Transcriptomics, Transcription,
        GeneExpression, RNASeq, Microarray, Proteomics, Metabolomics,
        MassSpectrometry,
BugReports: https://github.com/bhagwataditya/autonomics/issues
RoxygenNote: 7.3.1
Depends: R (>= 4.0)
Imports: abind, BiocFileCache, BiocGenerics, bit64, cluster,
        codingMatrices, colorspace, data.table, dplyr, edgeR, ggforce,
        ggplot2, ggrepel, graphics, grDevices, grid, gridExtra, limma,
        magrittr, matrixStats, methods, MultiAssayExperiment, parallel,
        RColorBrewer, rlang, R.utils, readxl, S4Vectors, scales, stats,
        stringi, SummarizedExperiment, tidyr, tidyselect, tools, utils,
        vsn
Suggests: affy, AnnotationDbi, AnnotationHub, apcluster, Biobase,
        BiocManager, BiocStyle, Biostrings, diagram, DBI, e1071,
        ensembldb, GenomicDataCommons, GenomicRanges, GEOquery,
        hgu95av2.db, ICSNP, jsonlite, knitr, lme4, lmerTest, MASS,
        patchwork, mixOmics, mpm, nlme, OlinkAnalyze, org.Hs.eg.db,
        org.Mm.eg.db, pcaMethods, pheatmap, progeny, propagate, RCurl,
        RSQLite, remotes, rmarkdown, ropls, Rsubread, readODS,
        rtracklayer, statmod, survival, survminer, testthat,
        UniProt.ws, writexl, XML
git_url: https://git.bioconductor.org/packages/autonomics
git_branch: RELEASE_3_20
git_last_commit: c729bba
git_last_commit_date: 2024-11-26
Repository: Bioconductor 3.20
Date/Publication: 2024-11-28
NeedsCompilation: no
Packaged: 2024-11-28 22:03:55 UTC; biocbuild
Author: Aditya Bhagwat [aut, cre],
  Richard Cotton [ctb],
  Shahina Hayat [ctb],
  Laure Cougnaud [ctb],
  Witold Szymanski [ctb],
  Vanessa Beutgen [ctb],
  Willem Ligtenberg [ctb],
  Hinrich Goehlmann [ctb],
  Karsten Suhre [ctb],
  Johannes Graumann [aut, sad]
Maintainer: Aditya Bhagwat <aditya.bhagwat@uni-marburg.de>
Built: R 4.4.2; ; 2024-11-29 17:16:18 UTC; unix
