Statistical approaches applicable in managing OMICS data: Urinary proteomics as exemplary case.

Publisher: Wiley Country of Publication: United States NLM ID: 8219702 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1098-2787 (Electronic) Linking ISSN: 02777037 NLM ISO Abbreviation: Mass Spectrom Rev Subsets: MEDLINE

Original Publication: New York : Wiley, [c1982-

Proteomics*/methods ; Biomarkers*/urine; Humans ; Machine Learning ; Workflow ; Mass Spectrometry/methods ; Data Interpretation, Statistical ; Software

With urinary proteomics profiling (UPP) as exemplary omics technology, this review describes a workflow for the analysis of omics data in large study populations. The proposed workflow includes: (i) planning omics studies and sample size considerations; (ii) preparing the data for analysis; (iii) preprocessing the UPP data; (iv) the basic statistical steps required for data curation; (v) the selection of covariables; (vi) relating continuously distributed or categorical outcomes to a series of single markers (e.g., sequenced urinary peptide fragments identifying the parental proteins); (vii) showing the added diagnostic or prognostic value of the UPP markers over and beyond classical risk factors, and (viii) pathway analysis to identify targets for personalized intervention in disease prevention or treatment. Additionally, two short sections respectively address multiomics studies and machine learning. In conclusion, the analysis of adverse health outcomes in relation to omics biomarkers rests on the same statistical principle as any other data collected in large population or patient cohorts. The large number of biomarkers, which have to be considered simultaneously requires planning ahead how the study database will be structured and curated, imported in statistical software packages, analysis results will be triaged for clinical relevance, and presented.
(© 2023 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd.)

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Keywords: multidimensional classifiers; proteomics; statistical methods; urinary proteomics

0 (Biomarkers)

Date Created: 20230505 Date Completed: 20241008 Latest Revision: 20241008

20241008

10.1002/mas.21849

37143314