Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data
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Advances in multiplexed single-cell immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) imaging technologies have enabled the analysis of cell-to-cell spatial relationships that promise to revolutionize our understanding of tissue-based diseases and autoimmune disorders. Multiplex images are collected as multichannel TIFF files; then denoised, segmented to identify cells and nuclei, normalized across slides with protein markers to correct for batch effects, and phenotyped; and then tissue composition and spatial context at the cellular level are analyzed. This chapter discusses methods and software infrastructure for image processing and statistical analysis of mIF/mIHC data.
Soupir A, Gadiyar I, Helm B, Harris C, Vandekar S, Peres L Stat Data Sci Imaging. 2025; 2(1).
PMID: 40051984 PMC: 11883755. DOI: 10.1080/29979676.2024.2437947.
Samorodnitsky S, Campbell K, Little A, Ling W, Zhao N, Chen Y bioRxiv. 2025; .
PMID: 39764056 PMC: 11702633. DOI: 10.1101/2024.12.18.628976.
mxfda: a comprehensive toolkit for functional data analysis of single-cell spatial data.
Wrobel J, Soupir A, Hayes M, Peres L, Vu T, Leroux A Bioinform Adv. 2024; 4(1):vbae155.
PMID: 39552929 PMC: 11568348. DOI: 10.1093/bioadv/vbae155.
Statistical analysis of multiple regions-of-interest in multiplexed spatial proteomics data.
Samorodnitsky S, Wu M Brief Bioinform. 2024; 25(6).
PMID: 39428129 PMC: 11491162. DOI: 10.1093/bib/bbae522.
A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data.
Samorodnitsky S, Campbell K, Ribas A, Wu M Bioinformatics. 2024; 40(7).
PMID: 38950184 PMC: 11257711. DOI: 10.1093/bioinformatics/btae425.