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EpiMix: an integrative tool for epigenomic subtyping using DNA methylation.
Zheng, Yuanning; Jun, John; Brennan, Kevin; Gevaert, Olivier.
Afiliación
  • Zheng Y; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
  • Jun J; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
  • Brennan K; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
  • Gevaert O; Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
bioRxiv ; 2023 Jan 04.
Article en En | MEDLINE | ID: mdl-36711917
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer, immunological, and cardiovascular diseases. Recent technological advances enable genome-wide quantification of DNAme in large human cohorts. So far, existing methods have not been evaluated to identify differential DNAme present in large and heterogeneous patient cohorts. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared to existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs. Using cell-type specific data from two separate studies, we discovered novel epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven non-coding RNAs in non-small cell lung cancer.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos