Package: gCMAP
Type: Package
Title: Tools for Connectivity Map-like analyses
Version: 1.6.0
Date: 2013-07-31
Depends: GSEABase, limma (>= 3.15.14)
Imports: Biobase, BiocGenerics, methods, GSEAlm, Category, Matrix (>=
        1.0.9), parallel, annotate, genefilter, AnnotationDbi
Suggests: DESeq, KEGG.db, reactome.db, RUnit, GO.db, mgsa
Enhances: bigmemory, bigmemoryExtras (>= 1.1.2)
Author: Thomas Sandmann <sandmann.thomas@gene.com>, Richard Bourgon
	<bourgon.richard@gene.com> and Sarah Kummerfeld
	<kummerfeld.sarah@gene.com>
Maintainer: Thomas Sandmann <sandmann.thomas@gene.com>
Description: 
  The gCMAP package provides a toolkit for comparing differential gene
  expression profiles through gene set enrichment analysis. Starting
  from normalized microarray or RNA-seq gene expression values (stored
  in lists of ExpressionSet and CountDataSet objects) the package
  performs differential expression analysis using the limma or DESeq
  packages. Supplying a simple list of gene identifiers, global
  differential expression profiles or data from complete experiments
  as input, users can use a unified set of several well-known gene set
  enrichment analysis methods to retrieve experiments with similar
  changes in gene expression. To take into account the directionality
  of gene expression changes, gCMAPQuery introduces the SignedGeneSet
  class, directly extending GeneSet from the GSEABase package.  To
  increase performance of large queries, multiple gene sets are stored
  as sparse incidence matrices within CMAPCollection eSets. gCMAP
  offers implementations of 1. Fisher's exact test (Fisher, J R Stat
  Soc, 1922) 2. The "connectivity map" method (Lamb et al, Science,
  2006) 3. Parametric and non-parametric t-statistic summaries (Jiang
  & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney
  rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as
  wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012)
  6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from
  the limma package and 7. wraps the gsea method from the mgsa package 
  (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4
  class inheriting from AnnotatedDataFrame, containing enrichment
  statistics as well as annotation data and providing simple
  high-level summary plots.
License: Artistic-2.0
LazyLoad: yes
ByteCompile: TRUE
biocViews: Bioinformatics, Microarray, Software, Pathways, Annotation
Collate: 'AllClasses.R' 'AllGenerics.R' 'SignedGeneSet-accessors.R'
        'utility-functions.R' 'camera_score-methods.R'
        'connectivity_score-methods.R' 'featureScore-methods.R'
        'fisher_score-methods.R' 'geneIndex-methods.R'
        'gsealm_jg_score-methods.R' 'gsealm_score-methods.R'
        'incidence-methods.R' 'mgsa_score-methods.R'
        'mapIdentifiers-methods.R' 'minSetSize-methods.R'
        'mroast_score-methods.R' 'romer_score-methods.R'
        'wilcox_score-methods.R' 'CMAPCollection-accessors.R'
        'CMAPResults-accessors.R'
Packaged: 2013-10-15 08:08:38 UTC; biocbuild
Built: R 3.0.2; ; 2013-10-15 15:17:23 UTC; windows
