A novel approach toward optimal workflow selection for DNA methylation biomarker discovery.

Autor: Nazer N; Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran., Sepehri MH; Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran., Mohammadzade H; Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran., Mehrmohamadi M; Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran. mehrmohamadi@ut.ac.ir.
Jazyk: angličtina
Zdroj: BMC bioinformatics [BMC Bioinformatics] 2024 Jan 23; Vol. 25 (1), pp. 37. Date of Electronic Publication: 2024 Jan 23.
DOI: 10.1186/s12859-024-05658-0
Abstrakt: DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.
(© 2024. The Author(s).)
Databáze: MEDLINE
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