2026-04-17T07:33:44Zhttps://recercat.cat/oai/request
oai:recercat.cat:2445/2250342026-04-10T21:57:58Zcom_2072_1057col_2072_478799col_2072_478917
RECERCAT author Lin, Yu-Yu author Breuer, Kersten author Weichenhan, Dieter author Lafrenz, Pascal author Sarnataro, Antonella author Wilk, Agata author Chepeleva, Maryna author Mücke, Oliver author Schönung, Maximilian author Petermann, Franziska author Kensche, Philip Reiner author Weiser, Lena author Thommen, Frank author Giacomelli, Gideon author Nordstroem, Karl author Gonzalez-Avalos, Edahi author Merkel, Angelika author Kretzmer, Helene author Fischer, Jonas author Krämer, Stephen author Iskar, Murat author Wolf, Stephan author Buchhalter, Ivo author Esteller, Manel, 1968- author Lawerenz, Christian author Twardziok, Sven author Zapatka, Marc author Hovestadt, Volker author Schlesner, Matthias author Schulz, Marcel H. author Hoffmann, Steve author Gerhauser, Clarissa author Walter, Jörn author Hartmann, Mark author Lipka, Daniel B. author Assenov, Yassen author Bock, Christoph author Plass, Christoph author Toth, Reka author Lutsik, Pavlo 2025-12-17T16:26:58Z2025-12-17T16:26:58Z2025-10-212025-12-17T16:26:58Z DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposures, and disease. Whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods remains the reference method for DNA methylation profiling genome-wide. While numerous software tools facilitate processing of DNA methylation sequencing reads, a comprehensive benchmarking study has been lacking. In this study, we systematically compared complete computational workflows for processing DNA methylation sequencing data using a dedicated benchmarking dataset generated with five whole-genome profiling protocols. As an evaluation reference, we employed accurate locus-specific measurements from our previous benchmark of targeted DNA methylation assays. Based on this experimental gold-standard assessment and multiple performance metrics, we identified workflows that consistently demonstrated superior performance and revealed major workflow development trends. To ensure the long-term utility of our benchmark, we implemented an interactive workflow execution and data presentation platform, adaptable to user-defined criteria and readily expandable to future software. cc-by (c) Lin, Y.Y. et al., 2025 https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Biologia computacional Seqüència de nucleòtids Epigènesi Computational biology Nucleotide sequence Epigenesis Pipeline Olympics: continuable benchmarking of computational workflows for DNA methylation sequencing data against an experimental gold standard info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion