Package: POMA 1.15.0

Pol Castellano-Escuder

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:Pol Castellano-Escuder [aut, cre]

POMA_1.15.0.tar.gz
POMA_1.15.0.zip(r-4.5)POMA_1.15.0.zip(r-4.4)POMA_1.15.0.zip(r-4.3)
POMA_1.15.0.tgz(r-4.4-any)POMA_1.15.0.tgz(r-4.3-any)
POMA_1.15.0.tar.gz(r-4.5-noble)POMA_1.15.0.tar.gz(r-4.4-noble)
POMA_1.15.0.tgz(r-4.4-emscripten)POMA_1.15.0.tgz(r-4.3-emscripten)
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'))

Peer review:

Bug tracker:https://github.com/pcastellanoescuder/poma/issues

Datasets:
  • st000284 - Colorectal Cancer Detection Using Targeted Serum Metabolic Profiling
  • st000336 - Targeted LC/MS of urine from boys with DMD and controls

On BioConductor:POMA-1.15.0(bioc 3.20)POMA-1.14.0(bioc 3.19)

bioconductor-package

32 exports 1.31 score 185 dependencies 20 mentions

Last updated 2 months agofrom:7623cc51af

Exports:%>%poma_pal_cpoma_pal_dPomaBatchPomaBoxplotsPomaClustPomaCorrPomaCreateObjectPomaDensityPomaDESeqPomaHeatmapPomaImputePomaLassoPomaLimmaPomaLMPomaLMMPomaNormPomaOddsRatioPomaOutliersPomaPCAPomaPCRPomaPLSPomaRandForestPomaRankProdPomaUMAPPomaUnivariatePomaVolcanoscale_color_poma_cscale_color_poma_dscale_fill_poma_cscale_fill_poma_dtheme_poma

Dependencies:abindannotateAnnotationDbiaskpassbackportsBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootbroomcachemcarcarDatacaretcirclizeclasscliclockclueclustercodetoolscolorspaceComplexHeatmapcorpcorcpp11crayoncurldata.tableDBIdbscanDelayedArrayDESeq2diagramdigestdoParalleldplyrdqrngdunn.teste1071edgeRellipseellipsisfansifarverfastmapFNNforeachformatRFSAfutile.loggerfutile.optionsfuturefuture.applygenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGetoptLongggplot2ggrepelglmnetGlobalOptionsglobalsgluegmpgowergridExtragtablehardhathmshttrigraphimputeipredIRangesirlbaisobanditeratorsjanitorjsonliteKEGGRESTKernSmoothlabelinglambda.rlatticelavalifecyclelimmalistenvlme4lmtestlocfitlubridatemagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmimeminqamixOmicsModelMetricsmunsellnlmenloptrnnetnumDerivopensslparallellypbkrtestpermutepillarpkgconfigplogrplotrixplyrpngpROCprodlimprogressrproxypurrrquantregR6randomForestRankProdrARPACKRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppProgressrecipesreshape2rjsonrlangRmpfrrpartRSpectraRSQLiteS4ArraysS4VectorsscalesshapesitmosnakecasesnowSparseArraySparseMSQUAREMstatmodstringistringrSummarizedExperimentsurvivalsvasystibbletidyrtidyselecttimechangetimeDatetzdbUCSC.utilsutf8uwotvctrsveganviridisLitewithrXMLxtableXVectorzlibbioczoo

Get Started

Pol Castellano-Escuder, Ph.D.

Rendered fromPOMA-workflow.Rmdusingknitr::rmarkdownon Jun 22 2024.

Last update: 2024-01-21
Started: 2023-12-08

Normalization Methods

Pol Castellano-Escuder, Ph.D.

Rendered fromPOMA-normalization.Rmdusingknitr::rmarkdownon Jun 22 2024.

Last update: 2023-12-14
Started: 2020-02-09

Readme and manuals

Help Manual

Help pageTopics
Box-Cox Transformationbox_cox_transformation
Correlation P-Valuescor_pmat
Detect decimalsdetect_decimals
Flatten Correlation MatrixflattenCorrMatrix
Return function to interpolate a continuous POMA color palettepoma_pal_c
Return function to interpolate a discrete POMA color palettepoma_pal_d
Batch CorrectionPomaBatch
Boxplots and Violin PlotsPomaBoxplots
Cluster AnalysisPomaClust
Correlation AnalysisPomaCorr
Create a 'SummarizedExperiment' ObjectPomaCreateObject
Density PlotsPomaDensity
Differential Expression Analysis Based on the Negative Binomial DistributionPomaDESeq
Heatmap PlotPomaHeatmap
Impute Missing ValuesPomaImpute
Lasso, Ridge, and Elasticnet Regularized Generalized Linear Models for Binary OutcomesPomaLasso
Differential Expression Analysis Using 'limma'PomaLimma
Linear ModelsPomaLM
Linear Mixed ModelsPomaLMM
Normalize DataPomaNorm
Logistic Regression Model Odds RatiosPomaOddsRatio
Analyse and Remove Statistical OutliersPomaOutliers
Principal Components AnalysisPomaPCA
Principal Components RegressionPomaPCR
Partial Least Squares MethodsPomaPLS
Classification Random ForestPomaRandForest
Rank Product/Rank Sum AnalysisPomaRankProd
Dimensionality Reduction with UMAPPomaUMAP
Univariate Statistical TestPomaUnivariate
Volcano PlotPomaVolcano
Sample Quantile Normalizationquantile_norm
Color scale constructor for continuous 'viridis' "plasma" palettescale_color_poma_c
Color scale constructor for discrete 'viridis' "plasma" palettescale_color_poma_d
Fill scale constructor for continuous 'viridis' "plasma" palettescale_fill_poma_c
Fill scale constructor for discrete 'viridis' "plasma" palettescale_fill_poma_d
Colorectal Cancer Detection Using Targeted Serum Metabolic Profilingst000284
Targeted LC/MS of urine from boys with DMD and controlsst000336
Sample Sum Normalizationsum_norm
A ggplot theme which allow custom yet consistent styling of plots in the POMA package and web app.theme_poma