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 (3.17)

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>

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

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("POMA")

 

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

Details

biocViews	BatchEffect, Classification, Clustering, DecisionTree, DimensionReduction, MultidimensionalScaling, Normalization, Preprocessing, PrincipalComponent, RNASeq, Regression, Software, StatisticalMethod, Visualization
Version	1.9.0
In Bioconductor since	BioC 3.12 (R-4.0) (2 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	POMA_1.9.0.tar.gz
Windows Binary
macOS Binary (x86_64)
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
Package Short Url	https://bioconductor.org/packages/POMA/
Package Downloads Report	Download Stats