# Bioconductor Msnbase

MSnbase provides infrastructure for manipulation, processing and visualisation of mass...

- Repository: https://github.com/bioMate-AI/biomate-bioconductor-kb (793 stars)
- Category: DevOps
- License: see repository
- Last updated: 2026-06-20
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-msnbase -g -a claude-code -y`
Codex: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-msnbase -g -a codex -y`
Cursor: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-msnbase -g -a cursor -y`
Gemini CLI: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-msnbase -g -a gemini-cli -y`

## Description

MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# MSnbase, Comprehensive Skill Guide

> **Domain:** Proteomics / Mass spectrometry
> **Bioconductor:** [MSnbase](https://bioconductor.org/packages/release/bioc/html/MSnbase.html)
> **Paper:** Gatto L, Lilley KS (2012). Bioinformatics, 28(2):288-289.

Infrastructure for mass spectrometry data handling in R: reading mzML/mzXML/mzData files, spectral processing, quantification, and proteomics/metabolomics workflows.

## Dependencies & Environment

> Package-intrinsic requirements from the Bioconductor landing page, reproduce in any R environment.

- **Version:** 2.37.0 · **Bioconductor:** 3.23 · **R:** ≥ 4.6
- **Depends:** BiocGenerics, Biobase, mzR, S4Vectors, ProtGenerics
- **Imports:** MsCoreUtils, PSMatch, BiocParallel, IRanges, plyr, vsn, affy, impute, pcaMethods, MALDIquant, mzID, digest, lattice, ggplot2, scales, MASS, Rcpp
- **Install:** `BiocManager::install("MSnbase")`

## When to Use

- Read mzML/mzXML files into R for proteomics or metabolomics workflows
- Process MS2 spectra: deisotoping, centroiding, filtering
- TMT/iTRAQ isobaric quantification
- Feature quantification from LC-MS data

**Alternatives:** `Spectra (modern successor)`, `openms (Python/C++)`, `msqrob2 (DE protein)`

## Do NOT Use When

- Large-scale DIA proteomics, use PyProphet/OpenSWATH or Spectronaut.
- Metabolomics spectral matching, use Spectra + CompoundDb instead.
- New projects, consider Spectra as the modern successor.

## Data Requirements

| Requirement | Details |
|-------------|----------|
| **Input Format** | mzML, mzXML, mzData (open MS formats; convert with ProteoWizard) |
| **Notes** | Use mode='onDisk' for files > 1GB to avoid memory issues |

## Installation

```r
if (!require("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("MSnbase")
library(MSnbase)
```

## Workflows

### Read and Process LC-MS Data for Proteomics
*Load mzML files, filter spectra, and perform isobaric quantification*

#### Read mzML files (on-disk mode)

The rest: https://github.com/bioMate-AI/biomate-bioconductor-kb/blob/HEAD/skills/proteomics/msnbase/SKILL.md