msBayesImpute

msBayesImpute is a versatile framework for handling missing values in mass spectrometry (MS) proteomics data.
It integrates probabilistic dropout models into a Bayesian matrix factorization framework, enabling robust, data-driven imputation.

Key features:

• Models both missing at random (MAR) and missing not at random (MNAR) values.
• Learns dropout curves directly from the data, without predefined assumptions.
• Works on both small and large datasets.
• Available in Python, R, and via a Shiny web interface.

This repository contains the R package of msBayesImpute, which is a wrapper of the Python implementation. msBayesImpute (Python implementation).

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Repository structure

msBayesImpute/
├── data/          # Example dataset (HeLa cell line proteomics data)
├── R/             # R wrapper scripts
├── man/           # Documentation for R functions
├── vignettes/     # Usage examples (see quick_guide_R.Rmd)
├── rshiny/        # Shiny web interface
├── msbayesimputepy-0.1.0-py3-none-any.whl   # Python wheel (remove before Bioconductor submission)
└── README.md

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Installation

Python package

Install the Python package using pip (the .whl file is provided in this repository):

pip install msbayesimputepy-0.1.0-py3-none-any.whl

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R package

Install the R package from source:

devtools::install_github("Lu-Group-UKHD/msBayesImpute")

Note: The R package uses the Python backend via reticulate.
Please ensure that the Python environment specified in reticulate matches the one where msbayesimputepy was installed. Instructions for setting the Python environment can be found in the vignette quick_guide_R.Rmd.

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Getting started

• See the vignette quick_guide_R.Rmd for a step-by-step guide to running msBayesImpute in R.
• A Shiny app is provided in the rshiny/ folder for users who prefer a graphical interface.

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Citation

If you use msBayesImpute in your research, please cite:
He J, et al. bioRxiv (2025). msBayesImpute: A Versatile Framework for Addressing Missing Values in Biomedical Mass Spectrometry Proteomics Data

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