Package: autoGO 0.9.1

Fabio Ticconi

autoGO: Auto-GO: Reproducible, Robust and High Quality Ontology Enrichment Visualizations

Auto-GO is a framework that enables automated, high quality Gene Ontology enrichment analysis visualizations. It also features a handy wrapper for Differential Expression analysis around the 'DESeq2' package described in Love et al. (2014) <doi:10.1186/s13059-014-0550-8>. The whole framework is structured in different, independent functions, in order to let the user decide which steps of the analysis to perform and which plot to produce.

Authors:Isabella Grassucci [aut], Eleonora Sperandio [aut], Fabio Ticconi [cre], Alice Massacci [aut], Lorenzo D'Ambrosio [aut], Matteo Pallocca [aut]

autoGO_0.9.1.tar.gz
autoGO_0.9.1.zip(r-4.5)autoGO_0.9.1.zip(r-4.4)autoGO_0.9.1.zip(r-4.3)
autoGO_0.9.1.tgz(r-4.4-any)autoGO_0.9.1.tgz(r-4.3-any)
autoGO_0.9.1.tar.gz(r-4.5-noble)autoGO_0.9.1.tar.gz(r-4.4-noble)
autoGO_0.9.1.tgz(r-4.4-emscripten)autoGO_0.9.1.tgz(r-4.3-emscripten)
autoGO.pdf |autoGO.html
autoGO/json (API)

# Install 'autoGO' in R:
install.packages('autoGO', repos = c('https://mpallocc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mpallocc/auto-go/issues

Datasets:

On CRAN:

11 exports 2 stars 1.19 score 144 dependencies 3 scripts 309 downloads

Last updated 6 months agofrom:8e56f1dfa6. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 05 2024
R-4.5-winOKSep 05 2024
R-4.5-linuxOKSep 05 2024
R-4.4-winOKSep 05 2024
R-4.4-macOKSep 05 2024
R-4.3-winOKAug 06 2024
R-4.3-macOKAug 06 2024

Exports:autoGObarplotGOchoose_databasedeseq_analysisfiltering_DEheatmapGOlolliGOread_enrich_tablesread_gene_listsssgsea_wrappervolcanoplot

Dependencies:abindannotateAnnotationDbiapeaskpassbabelgenebeachmatBHBiobaseBiocFileCacheBiocGenericsBiocParallelBiocSingularBiostringsbitbit64blobcachemcirclizeclicliprclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsDESeq2dichromatdigestdoParalleldplyrenrichRfansifarverfastmapfilelockforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggplot2ggrepelGlobalOptionsgluegraphGSEABaseGSVAgtableHDF5ArrayhmshttrimguRIRangesirlbaisobanditeratorsjpegjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelocfitmagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemsigdbrmunsellnlmeopensslopenxlsxpillarpkgconfigplogrplyrpngprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloreadrreshape2rhdf5rhdf5filtersRhdf5librjsonrlangRSQLitersvdS4ArraysS4VectorsScaledMatrixscalesshapeSingleCellExperimentslamsnowSparseArraysparseMatrixStatsSpatialExperimentstringistringrSummarizedExperimentsystextshapetibbletidyrtidyselecttzdbUCSC.utilsutf8vctrsviridisLitevroomwithrWriteXLSXMLxtableXVectorzipzlibbioc

AutoGO: Reproducible, Robust and High Quality Ontology Enrichment Visualizations

Rendered fromautoGO-tutorial.Rmdusingknitr::rmarkdownon Sep 05 2024.

Last update: 2024-03-08
Started: 2022-11-18