Package: edge 2.45.0

John D. Storey

edge: Extraction of Differential Gene Expression

The edge package implements methods for carrying out differential expression analyses of genome-wide gene expression studies. Significance testing using the optimal discovery procedure and generalized likelihood ratio tests (equivalent to F-tests and t-tests) are implemented for general study designs. Special functions are available to facilitate the analysis of common study designs, including time course experiments. Other packages such as sva and qvalue are integrated in edge to provide a wide range of tools for gene expression analysis.

Authors:John D. Storey, Jeffrey T. Leek and Andrew J. Bass

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
edge/json (API)

# Install 'edge' in R:

install.packages('edge', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jdstorey/edge/issues

Datasets:

endotoxin - Gene expression dataset from Calvano et al. (2005) Nature
gibson - Gene expression dataset from Idaghdour et al.
kidney - Gene expression dataset from Rodwell et al.

On BioConductor:edge-2.45.0(bioc 3.24)edge-2.44.0(bioc 3.23)

multiplecomparison differentialexpression timecourse regression geneexpression dataimport

7.77 score 21 stars 94 scripts 16 mentions 29 exports 77 dependencies

Last updated from:92259f8fb4. Checks:1 ERROR, 11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	173
linux-devel-arm64	NOTE	245
linux-devel-x86_64	NOTE	293
source / vignettes	OK	271
linux-release-arm64	NOTE	270
linux-release-x86_64	NOTE	284
macos-release-arm64	NOTE	171
macos-release-x86_64	NOTE	290
macos-oldrel-arm64	NOTE	137
macos-oldrel-x86_64	NOTE	304
windows-devel	NOTE	252
windows-release	NOTE	220
windows-oldrel	NOTE	216
wasm-release	OK	169

Exports:apply_qvalue apply_sva betaCoef build_models build_study deSet fit_models fitFull fitNull fullMatrix fullMatrix<-fullModel fullModel<-individual individual<-kl_clust lrt nullMatrix nullMatrix<-nullModel nullModel<-odp qvalueObj qvalueObj<-resFull resNull show sType summary

Dependencies:annotate AnnotationDbi askpass BH Biobase BiocGenerics BiocParallel Biostrings bit bit64 blob cachem cli codetools cpp11 crayon curl DBI edgeR farver fastmap formatR futile.logger futile.options genefilter generics ggplot2 glue gtable httr IRanges isoband jsonlite KEGGREST labeling lambda.r lattice lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime nlme openssl pkgconfig plyr png qvalue R6 RColorBrewer Rcpp reshape2 rlang RSQLite S4Vectors S7 scales Seqinfo snow statmod stringi stringr survival sva sys vctrs viridisLite withr XML xtable XVector

edge Package

Rendered fromedge.Rnwusingknitr::knitr

Last update: 2024-03-27
Started: 2015-04-14

Help page	Topics
Estimate the q-values for a given set of p-values	apply_qvalue apply_qvalue,deSet-method
Estimate surrogate variables	apply_sva apply_sva,deSet-method
Regression coefficients from full model fit	betaCoef betaCoef,deFit-method
Generate a deSet object with full and null models	build_models
Formulates the experimental models	build_study
The differential expression class for the model fits	deFit-class
Create a deSet object from an ExpressionSet	deSet deSet,ExpressionSet-method
The differential expression class (deSet)	deSet-class
Extraction of Differential Gene Expression	edge-package edge
Gene expression dataset from Calvano et al. (2005) Nature	endotoxin
Linear regression of the null and full models	fit_models fit_models,deSet-method
Fitted data from the full model	fitFull fitFull,deFit-method
Fitted data from the null model	fitNull fitNull,deFit-method
Matrix representation of full model	fullMatrix fullMatrix,deSet-method fullMatrix<- fullMatrix<-,deSet-method
Full model equation	fullModel fullModel,deSet-method fullModel<- fullModel<-,deSet-method
Gene expression dataset from Idaghdour et al. (2008)	gibson
Individuals sampled in experiment	individual individual,deSet-method individual<- individual<-,deSet-method
Gene expression dataset from Rodwell et al. (2004)	kidney
Modular optimal discovery procedure (mODP)	kl_clust kl_clust,deSet,deFit-method kl_clust,deSet,missing-method
Performs F-test (likelihood ratio test using Normal likelihood)	lrt lrt,deSet,deFit-method lrt,deSet,missing-method
Matrix representation of null model	nullMatrix nullMatrix,deSet-method nullMatrix<- nullMatrix<-,deSet-method
Null model equation from deSet object	nullModel nullModel,deSet-method nullModel<- nullModel<-,deSet-method
The optimal discovery procedure	odp odp,deSet,deFit-method odp,deSet,missing-method
Access/set qvalue slot	qvalueObj qvalueObj,deSet-method qvalueObj<- qvalueObj<-,deSet-method
Residuals of full model fit	resFull resFull,deFit-method
Residuals of null model fit	resNull resNull,deFit-method
Show function for deFit and deSet	show show,deFit-method show,deSet-method
Statistic type used in analysis	sType sType,deFit-method
Summary of deFit and deSet	summary summary,deFit-method summary,deSet-method

Package: edge 2.45.0

edge: Extraction of Differential Gene Expression

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