Pro-MAP: a robust pipeline for the pre-processing of single channel protein microarray data
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Department of Integrated Biomedical Sciences, Division of Chemical and Systems Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.Issue Date
2022
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Background: The central role of proteins in diseases has made them increasingly attractive as therapeutic targets and indicators of cellular processes. Protein microarrays are emerging as an important means of characterising protein activity. Their accurate downstream analysis to produce biologically significant conclusions is largely dependent on proper pre-processing of extracted signal intensities. However, existing computational tools are not specifically tailored to the nature of these data and lack unanimity. Results: Here, we present the single-channel Protein Microarray Analysis Pipeline, a tailored computational tool for analysis of single-channel protein microarrays enabling biomarker identification, implemented in R, and as an interactive web application. We compared four existing background correction and normalization methods as well as three array filtering techniques, applied to four real datasets with two microarray designs, extracted using two software programs. The normexp, cyclic loess, and array weighting methods were most effective for background correction, normalization, and filtering respectively. Conclusions: Thus, here we provided a versatile and effective pre-processing and differential analysis workflow for single-channel protein microarray data in form of an R script and web application ( https://metaomics.uct.ac.za/shinyapps/Pro-MAP/ .) for those not well versed in the R programming language.Citation
Mowoe MO, Garnett S, Lennard K, Talbot J, Townsend P, Jonas E, et al. Pro-MAP: a robust pipeline for the pre-processing of single channel protein microarray data. BMC bioinformatics. 2022 Dec 9;23(1):534. PubMed PMID: 36494629. Pubmed Central PMCID: PMC9733281. Epub 2022/12/10. eng.Journal
BMC BioinformaticsDOI
10.1186/s12859-022-05095-xPubMed ID
36494629Additional Links
https://dx.doi.org/10.1186/s12859-022-05095-xType
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enae974a485f413a2113503eed53cd6c53
10.1186/s12859-022-05095-x
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