POMA

DOI: 10.18129/B9.bioc.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>

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

PDF		Reference Manual

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) (2.5 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
LinkingTo
Suggests	BiocStyle, covr, ggraph, knitr, patchwork, plotly, tidyverse, testthat (>= 2.3.2)
SystemRequirements
Enhances
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
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