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")):

Installation

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


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

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")

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

Need some help? Ask on the Bioconductor Support site!

Details

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) (3.5 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
System Requirements
URL	https://github.com/pcastellanoescuder/POMA
Bug Reports	https://github.com/pcastellanoescuder/POMA/issues

Suggests	BiocStyle, covr, ggraph, knitr, patchwork, plotly, tidyverse, testthat (>= 2.3.2)
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me	fobitools
Links To Me
Build Report	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/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.17	Source Archive