POMA introduces 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 uses the standardized SummarizedExperiment class to achieve the maximum flexibility and reproducibility and makes
POMA compatible with other Bioconductor packages.
POMA also has two different Shiny app modules both for exploratory data analysis and statistical analysis that implement all
POMA functions in two user-friendly web interfaces.
To install Bioconductor version:
# install.packages("BiocManager") BiocManager::install("POMA")
If you need the GitHub version (not recommended unless you know what you are doing), use:
# install.packages("devtools") devtools::install_github("pcastellanoescuder/POMA")
Please note that the ‘POMA’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.