# Bioconductor Mscoreutils

MsCoreUtils defines low-level functions for mass spectrometry data and is independent...

- Repository: https://github.com/bioMate-AI/biomate-bioconductor-kb (793 stars)
- Category: Engineering
- 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-mscoreutils -g -a claude-code -y`
Codex: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-mscoreutils -g -a codex -y`
Cursor: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-mscoreutils -g -a cursor -y`
Gemini CLI: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-mscoreutils -g -a gemini-cli -y`

## Description

MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning, baseline estimation),

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

# MsCoreUtils

## Dependencies & Environment

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

- **Version:** 1.24.0 · **Bioconductor:** 3.23 · **R:** ≥ 4.6
- **Imports:** S4Vectors, MASS, clue
- **Install:** `BiocManager::install("MsCoreUtils")`

## When to Use
- **Quantitative Aggregation**: Calculating the robust summary of matrix columns (e.g., summarizing peptide quantitation values into protein intensities) using `robustSummary()`.
- **Spectra Processing**: Performing low-level mass spectra processing such as noise estimation, smoothing, and binning using functions like `noise()`, `smooth()`, and `bin()`.
- **Missing Data Imputation**: Imputing missing data in quantitative matrices using methods like `impute_knn()`, `impute_RF()`, or `impute_matrix()`.
- **Data Normalization**: Normalizing data matrices using `normalize_matrix()`.

## When NOT to Use
- For high-level, formal data structure manipulation of MS data, use **Spectra** or **MSnbase** instead because `MsCoreUtils` only provides low-level functions independent of high-level data structures.
- For complete end-to-end LC-MS preprocessing workflows, use **xcms** instead because `MsCoreUtils` provides individual utility functions rather than a full pipeline.

## Data Requirements
- Basic R classes such as `matrix` or numeric vectors.
- For `robustSummary()`, a numeric `matrix` where columns represent samples and rows represent features (e.g., peptides).

## Key Parameters
- **x** (matrix): A numeric matrix provided to functions like `robustSummary()`.
- **nrow** (numeric): Number of rows when constructing a `matrix()` for testing or processing.

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