DOI: 10.18129/B9.bioc.POMA  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see POMA.

Tools for Omics Data Analysis

Bioconductor version: 3.17

A reproducible and easy-to-use toolkit for visualization, pre-processing, exploration, and statistical analysis of omics datasets. The main aim of POMA is to enable a flexible data cleaning and statistical analysis processes in one comprehensible and user-friendly R package. This package has a Shiny app version called POMAShiny that implements all POMA functions. See https://github.com/pcastellanoescuder/POMAShiny. See Castellano-Escuder P, González-Domínguez R, Carmona-Pontaque F, et al. (2021) for more details.

Author: Pol Castellano-Escuder [aut, cre]

Maintainer: Pol Castellano-Escuder <polcaes at gmail.com>

Citation (from within R, enter citation("POMA")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


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HTML R Script POMA EDA Example
HTML R Script POMA Normalization Methods
HTML R Script POMA Workflow
PDF   Reference Manual
Text   NEWS


biocViews BatchEffect, Classification, Clustering, DecisionTree, DimensionReduction, MultidimensionalScaling, Normalization, Preprocessing, PrincipalComponent, RNASeq, Regression, Software, StatisticalMethod, Visualization
Version 1.10.0
In Bioconductor since BioC 3.12 (R-4.0) (3 years)
License GPL-3
Depends R (>= 4.0)
Imports broom, caret, ComplexHeatmap, dbscan, dplyr, DESeq2, ggplot2, ggrepel, glasso (>= 1.11), glmnet, impute, limma, magrittr, mixOmics, randomForest, RankProd(>= 3.14), rmarkdown, SummarizedExperiment, tibble, tidyr, uwot, vegan
Suggests BiocStyle, covr, ggraph, knitr, patchwork, plotly, tidyverse, testthat (>= 2.3.2)
URL https://github.com/pcastellanoescuder/POMA
BugReports https://github.com/pcastellanoescuder/POMA/issues
Depends On Me
Imports Me
Suggests Me fobitools
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package POMA_1.10.0.tar.gz
Windows Binary POMA_1.10.0.zip (64-bit only)
macOS Binary (x86_64) POMA_1.10.0.tgz
macOS Binary (arm64) POMA_1.9.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/POMA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/POMA
Bioc Package Browser https://code.bioconductor.org/browse/POMA/
Package Short Url https://bioconductor.org/packages/POMA/
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