POMA

DOI: 10.18129/B9.bioc.POMA    

Tools for Omics Data Analysis

Bioconductor version: Release (3.16)

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 "4.2") 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 BatchEffect, Classification, Clustering, DecisionTree, DimensionReduction, MultidimensionalScaling, Normalization, Preprocessing, PrincipalComponent, RNASeq, Regression, Software, StatisticalMethod, Visualization
Version 1.8.0
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_1.8.0.tar.gz
Windows Binary POMA_1.8.0.zip
macOS Binary (x86_64) POMA_1.8.0.tgz
macOS Binary (arm64) POMA_1.8.0.tgz
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

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