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POMA

This is the development version of POMA; for the stable release version, see POMA.

Tools for Omics Data Analysis

Bioconductor version: Development (3.18)

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")):

Installation

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

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("POMA")

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

Documentation

Reference Manual PDF

Details

biocViews BatchEffect, Classification, Clustering, DecisionTree, DimensionReduction, MultidimensionalScaling, Normalization, Preprocessing, PrincipalComponent, RNASeq, Regression, Software, StatisticalMethod, Visualization
Version 1.11.0
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
Linking To
Suggests BiocStyle, covr, ggraph, knitr, patchwork, plotly, tidyverse, testthat (>= 2.3.2)
System Requirements
Enhances
URL https://github.com/pcastellanoescuder/POMA
Bug Reports https://github.com/pcastellanoescuder/POMA/issues
See More
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
Windows Binary POMA_1.11.0.zip
macOS Binary (x86_64) POMA_1.11.0.tgz
macOS Binary (arm64)
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/
Package Downloads Report Download Stats