Batch correction for large-scale mass spectrometry imaging experiments

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ID: 316057
2026
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Abstract
SUMMARY: We assess batch correction methods for MALDI mass spectrometry imaging experiments. ComBAT reduced batch-related technical variance, maintained biological variation, and improved the overall score by 19.4%. AVAILABILITY AND IMPLEMENTATION: Methods are available in R. comBAT is used through the "sva" package while Harmony, CCA, FastMNN are available in the "Seurat" package https://github.com/satijalab/seurat. scVI, scANVI are Scanorama are available in the Python programming language and through their github https://github.com/scverse/scvi-tools. Associated R code is found at DOI: https://doi.org/10.5281/zenodo.19730022. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7163677633 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Andreas Abildskov Sparre, Ole N Jensen
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag360
URL
https://doi.org/10.1093/bioinformatics/btag360
Keywords Keywords not found

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