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)
Author: Pol Castellano-Escuder [aut, cre]
Maintainer: Pol Castellano-Escuder <polcaes at gmail.com>
Citation (from within R,
enter citation("POMA")
):
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.
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 |
Reference Manual | ||
Text | NEWS |
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) (2.5 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 |
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 |
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 |
Bioc Package Browser | https://code.bioconductor.org/browse/POMA/ |
Package Short Url | https://bioconductor.org/packages/POMA/ |
Package Downloads Report | Download Stats |
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