Package: POMA 1.17.6
POMA: Tools for Omics Data Analysis
The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.
Authors:
POMA_1.17.6.tar.gz
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POMA_1.17.6.tgz(r-4.4-any)POMA_1.17.6.tgz(r-4.3-any)
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POMA.pdf |POMA.html✨
POMA/json (API)
NEWS
# Install 'POMA' in R: |
install.packages('POMA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pcastellanoescuder/poma/issues
On BioConductor:POMA-1.17.5(bioc 3.21)POMA-1.16.0(bioc 3.20)
batcheffectclassificationclusteringdecisiontreedimensionreductionmultidimensionalscalingnormalizationpreprocessingprincipalcomponentregressionrnaseqsoftwarestatisticalmethodvisualizationbioconductorbioinformaticsdata-visualizationdimension-reductionexploratory-data-analysismachine-learningomics-data-integrationpipelinepre-processingstatistical-analysisuser-friendlyworkflow
Last updated 24 days agofrom:09bb0156fa. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-win | NOTE | Nov 27 2024 |
R-4.5-linux | NOTE | Nov 27 2024 |
R-4.4-win | NOTE | Nov 27 2024 |
R-4.4-mac | NOTE | Nov 27 2024 |
R-4.3-win | NOTE | Nov 27 2024 |
R-4.3-mac | NOTE | Nov 27 2024 |
Exports:%>%poma_pal_cpoma_pal_dPomaBatchPomaBoxplotsPomaClustPomaCorrPomaCreateObjectPomaDensityPomaDESeqPomaEnrichmentPomaHeatmapPomaImputePomaLassoPomaLimmaPomaLMPomaLMMPomaNormPomaOddsRatioPomaOutliersPomaPCAPomaPCRPomaPLSPomaRandForestPomaRankProdPomaUMAPPomaUnivariatePomaVolcanoscale_color_poma_cscale_color_poma_dscale_fill_poma_cscale_fill_poma_dtheme_poma
Dependencies:abindannotateAnnotationDbiaskpassbabelgenebackportsbase64encBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootbroombslibcachemcarcarDatacaretcirclizeclasscliclockclueclustercodetoolscolorspaceComplexHeatmapcorpcorcowplotcpp11crayoncurldata.tableDBIdbscanDelayedArrayDerivDESeq2diagramdigestdoBydoParalleldplyrdqrngdunn.teste1071edgeRellipseevaluatefansifarverfastmapfastmatchfgseaFNNfontawesomeforeachformatRFormulafsFSAfutile.loggerfutile.optionsfuturefuture.applygenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggcorrplotggplot2ggrepelglmnetGlobalOptionsglobalsgluegmpgowergridExtragsignalgtablehardhathighrhmshtmltoolshtmlwidgetshttrigraphimputeipredIRangesirlbaisobanditeratorsjanitorjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlatticelavalifecyclelimmalistenvlme4lmtestlocfitlubridatemagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamixOmicsModelMetricsmodelrmsigdbrmultcompmunsellmvtnormnlmenloptrnnetnumDerivopensslparallellypbkrtestpermutepillarpkgconfigplogrplotrixplyrpngpracmapROCprodlimprogressrproxypurrrquantregR6randomForestRankProdrappdirsrARPACKRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppProgressrecipesreshape2rglrjsonrlangrmarkdownRmpfrrpartRSpectraRSQLiteS4ArraysS4VectorssandwichsassscalesshapesitmosnakecasesnowSparseArraySparseMSQUAREMstatmodstringistringrSummarizedExperimentsurvivalsvasysTH.datatibbletidyrtidyselecttimechangetimeDatetinytextzdbUCSC.utilsutf8uwotvctrsveganviridisLitewithrxfunXMLxtableXVectoryamlzlibbioczoo