POMA

DOI: 10.18129/B9.bioc.POMA    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see POMA.

User-friendly Workflow for Omics Data Analysis

Bioconductor version: 3.15

A structured, reproducible and easy-to-use workflow for the 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 also has a Shiny app version that implements all POMA functions. See https://github.com/pcastellanoescuder/POMAShiny.

Author: Pol Castellano-Escuder [aut, cre]

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

Installation

To install this package, start R (version "4.2") 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")

 

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

Details

biocViews	MassSpectrometry, Metabolomics, Normalization, Preprocessing, Proteomics, ReportWriting, Software, StatisticalMethod, Visualization
Version	1.6.0
In Bioconductor since	BioC 3.12 (R-4.0) (2 years)
License	GPL-3
Depends	R (>= 4.0)
Imports	broom, caret, ComplexHeatmap, dplyr, e1071, ggplot2, ggrepel, glasso (>= 1.11), glmnet, impute, knitr, limma, magrittr, mixOmics, randomForest, RankProd(>= 3.14), rmarkdown, SummarizedExperiment, tibble, tidyr, vegan
LinkingTo
Suggests	BiocStyle, covr, ggraph, 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_1.6.0.tar.gz
Windows Binary	POMA_1.6.0.zip
macOS Binary (x86_64)	POMA_1.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/POMA
Source Repository (Developer Access)	git clone [email protected]:packages/POMA
Package Short Url	https://bioconductor.org/packages/POMA/
Package Downloads Report	Download Stats