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.