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
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autoGO_0.9.1.tgz(r-4.4-any)autoGO_0.9.1.tgz(r-4.3-any)
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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:

3.90 score 2 stars 3 scripts 235 downloads 11 exports 145 dependencies

Last updated 9 months agofrom:8e56f1dfa6. Checks:OK: 6 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winOKNov 04 2024
R-4.5-linuxWARNINGNov 04 2024
R-4.4-winOKNov 04 2024
R-4.4-macOKNov 04 2024
R-4.3-winOKNov 04 2024
R-4.3-macOKNov 04 2024

Exports:autoGObarplotGOchoose_databasedeseq_analysisfiltering_DEheatmapGOlolliGOread_enrich_tablesread_gene_listsssgsea_wrappervolcanoplot

Dependencies:abindannotateAnnotationDbiapeaskpassassortheadbabelgenebeachmatBHBiobaseBiocFileCacheBiocGenericsBiocParallelBiocSingularBiostringsbitbit64blobcachemcirclizeclicliprclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsDESeq2dichromatdigestdoParalleldplyrenrichRfansifarverfastmapfilelockforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggplot2ggrepelGlobalOptionsgluegraphGSEABaseGSVAgtableHDF5ArrayhmshttrimguRIRangesirlbaisobanditeratorsjpegjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelocfitmagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemsigdbrmunsellnlmeopensslopenxlsxpillarpkgconfigplogrplyrpngprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloreadrreshape2rhdf5rhdf5filtersRhdf5librjsonrlangRSQLitersvdS4ArraysS4VectorsScaledMatrixscalesshapeSingleCellExperimentslamsnowSparseArraysparseMatrixStatsSpatialExperimentstringistringrSummarizedExperimentsystextshapetibbletidyrtidyselecttzdbUCSC.utilsutf8vctrsviridisLitevroomwithrWriteXLSXMLxtableXVectorzipzlibbioc

AutoGO: Reproducible, Robust and High Quality Ontology Enrichment Visualizations

Rendered fromautoGO-tutorial.Rmdusingknitr::rmarkdownon Nov 04 2024.

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