DOI: 10.18129/B9.bioc.POMA    

This is the development version of POMA; to use it, please install the devel version of Bioconductor.

User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Bioconductor version: Development (3.12)

POMA introduces a structured, reproducible and easy-to-use workflow for the visualization, pre-processing, exploratory and statistical analysis of mass spectrometry data. 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] , Raúl González-Domínguez [aut] , Cristina Andrés-Lacueva [aut] , Alex Sánchez-Pla [aut]

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

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


To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


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:



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


biocViews MassSpectrometry, Metabolomics, Normalization, Preprocessing, Proteomics, ReportWriting, Software, Visualization
Version 0.99.45
In Bioconductor since BioC 3.12 (R-4.0)
License GPL-3
Depends R (>= 4.0)
Imports Biobase, broom, caret, clisymbols, ComplexHeatmap, crayon, dplyr, e1071, ggcorrplot, ggplot2, ggraph, ggrepel, glasso (>= 1.11), glmnet, impute, knitr, limma, magrittr, mixOmics, MSnbase(>= 2.12), patchwork, plotly, qpdf, randomForest, RankProd(>= 3.14), reshape2, rmarkdown, tibble, tidyr, vegan
Suggests BiocStyle, covr, tidyverse, testthat (>= 2.3.2)
URL https://github.com/pcastellanoescuder/POMA
BugReports https://github.com/pcastellanoescuder/POMA/issues
Depends On Me
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Follow Installation instructions to use this package in your R session.

Source Package POMA_0.99.45.tar.gz
Windows Binary POMA_0.99.45.zip
macOS 10.13 (High Sierra) POMA_0.99.45.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/
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