Package: methylGSA 1.31.0

Xu Ren

methylGSA: Gene Set Analysis Using the Outcome of Differential Methylation

The main functions for methylGSA are methylglm and methylRRA. methylGSA implements logistic regression adjusting number of probes as a covariate. methylRRA adjusts multiple p-values of each gene by Robust Rank Aggregation. For more detailed help information, please see the vignette.

Authors:Xu Ren [aut, cre], Pei Fen Kuan [aut]

methylGSA_1.31.0.tar.gz
methylGSA_1.31.0.zip(r-4.7)methylGSA_1.31.0.zip(r-4.6)methylGSA_1.31.0.zip(r-4.5)
methylGSA_1.31.0.tgz(r-4.6-any)methylGSA_1.31.0.tgz(r-4.5-any)
methylGSA_1.31.0.tar.gz(r-4.7-any)methylGSA_1.31.0.tar.gz(r-4.6-any)
methylGSA_1.31.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
methylGSA/json (API)

# Install 'methylGSA' in R:

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

Bug tracker:https://github.com/reese3928/methylgsa/issues

Datasets:

cpg.pval - An example of user input cpg.pval
CpG2Gene - An example of user user-supplied mapping between CpGs and genes
GS.list - An example of user input gene sets

On BioConductor:methylGSA-1.31.0(bioc 3.24)methylGSA-1.30.0(bioc 3.23)

dnamethylation differentialmethylation genesetenrichment regression generegulation pathways enrichment generalized-linear-models logistic-regression methylation ontology shiny

7.19 score 13 stars 60 scripts 11 mentions 8 exports 226 dependencies

Last updated from:7792ec00a5. Checks:8 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	1322
linux-devel-x86_64	NOTE	1595
source / vignettes	OK	1327
linux-release-x86_64	NOTE	1607
macos-release-arm64	NOTE	807
macos-oldrel-arm64	NOTE	991
windows-devel	NOTE	1243
windows-release	NOTE	1189
windows-oldrel	NOTE	1306
wasm-release	OK	1345

Exports:barplot getDescription getGS methylglm methylgometh methylRRA prepareAnnot runExample

Dependencies:abind aisdk annotate AnnotationDbi ape aplot askpass base64 base64enc beanplot BH BiasedUrn Biobase BiocBaseUtils BiocFileCache BiocGenerics BiocIO biocmake BiocParallel Biostrings bit bit64 bitops blob bslib bumphunter cachem callr cigarillo cli clipr cluster clusterProfiler codetools commonmark cpp11 crayon curl data.table DBI dbplyr DelayedArray DelayedMatrixStats digest dir.expiry doRNG DOSE dplyr enrichit enrichplot evaluate farver fastmap FDb.InfiniumMethylation.hg19 filelock fontawesome fontBitstreamVera fontLiberation fontquiver foreach formatR fs futile.logger futile.options gdtools genefilter generics GenomeInfoDb GenomicAlignments GenomicFeatures GenomicRanges GEOquery ggforce ggfun ggiraph ggnewscale ggplot2 ggplotify ggrepel ggtangle ggtree glue GO.db GOSemSim gridExtra gridGraphics gson gtable h5mread HDF5Array highr hms htmltools htmlwidgets httpuv httr httr2 igraph IlluminaHumanMethylation450kanno.ilmn12.hg19 IlluminaHumanMethylation450kmanifest IlluminaHumanMethylationEPICanno.ilm10b4.hg19 IlluminaHumanMethylationEPICmanifest IlluminaHumanMethylationEPICv2anno.20a1.hg38 IlluminaHumanMethylationEPICv2manifest illuminaio IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling lambda.r later lattice lazyeval lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats mclust memoise methylumi mime minfi missMethyl multtest nlme nor1mix openssl org.Hs.eg.db otel patchwork pillar pkgconfig plyr png polyclip preprocessCore prettyunits processx progress promises ps purrr quadprog qvalue R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppEigen RCurl reactome.db readr rentrez reshape reshape2 restfulr rhdf5 rhdf5filters Rhdf5lib Rhtslib rjson rlang rmarkdown rngtools RobustRankAggreg Rsamtools RSQLite rtracklayer ruv rvest S4Arrays S4Vectors S7 sass scales scatterpie scrime selectr Seqinfo shiny siggenes snow sourcetools SparseArray sparseMatrixStats statmod stringi stringr SummarizedExperiment survival sys systemfonts tibble tidydr tidyr tidyselect tidytree tinytex treeio tweenr TxDb.Hsapiens.UCSC.hg19.knownGene tzdb UCSC.utils utf8 vctrs viridisLite vroom withr xfun XML xml2 xtable XVector yaml yulab.utils

methylGSA: Gene Set Analysis for DNA Methylation Datasets

Rendered frommethylGSA-vignette.Rmdusingknitr::rmarkdown

Last update: 2021-05-08
Started: 2018-06-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Barplot for methylGSA analysis result	barplot
An example of user input cpg.pval	cpg.pval
An example of user user-supplied mapping between CpGs and genes	CpG2Gene
Get CpG annotation	getAnnot
Get gene set description	getDescription
Get Gene Sets	getGS
An example of user input gene sets	GS.list
Implement logistic regression adjusting for number of probes in enrichment analysis	methylglm
Adjusting number of probes in gene set testing using gometh or gsameth in missMethyl	methylgometh
Enrichment analysis after adjusting multiple p-values of each gene by Robust Rank Aggregation	methylRRA
Prepare user-supplied mapping between CpGs and genes.	prepareAnnot
methylGSA shiny app	runExample