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Bioconductor - POMA

POMA

This is the released version of POMA; for the devel version, see POMA.

Tools for Omics Data Analysis

Bioconductor version: Release (3.21)

The POMA package offers a comprehensive toolkit designed for omics data analysis, streamlining the process from initial visualization to final statistical analysis. Its primary goal is to simplify and unify the various steps involved in omics data processing, making it more accessible and manageable within a single, intuitive R package. Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and replicability, making POMA an essential asset for researchers handling omics datasets. See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder et al. (2021) for more details.

Author: Pol Castellano-Escuder [aut, cre] ORCID: 0000-0001-6466-877X

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

Citation (from within R, enter citation("POMA")): Installation

To install this package, start R (version "4.5") 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")
Details biocViews BatchEffect, Classification, Clustering, DecisionTree, DimensionReduction, MultidimensionalScaling, Normalization, Preprocessing, PrincipalComponent, RNASeq, Regression, Software, StatisticalMethod, Visualization Version 1.18.0 In Bioconductor since BioC 3.12 (R-4.0) (4.5 years) License GPL-3 Depends R (>= 4.0) Imports broom, caret, ComplexHeatmap, dbscan, dplyr, DESeq2, fgsea, FSA, ggcorrplot, ggplot2, ggrepel, glmnet, grid, impute, janitor, limma, lme4, magrittr, MASS, mixOmics, multcomp, msigdbr, purrr, randomForest, RankProd(>= 3.14), rlang, SummarizedExperiment, sva, tibble, tidyr, utils, uwot, vegan System Requirements URL https://github.com/pcastellanoescuder/POMA Bug Reports https://github.com/pcastellanoescuder/POMA/issues See More Package Archives

Follow Installation instructions to use this package in your R session.

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