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CelFiE-ISH: a probabilistic model for multi-cell type deconvolution from single-molecule DNA methylation haplotypes.
Unterman, Irene; Avrahami, Dana; Katsman, Efrat; Triche, Timothy J; Glaser, Benjamin; Berman, Benjamin P.
Afiliación
  • Unterman I; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
  • Avrahami D; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
  • Katsman E; Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
  • Triche TJ; Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
  • Glaser B; Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI, USA.
  • Berman BP; Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel. ben.glaser@mail.huji.ac.il.
Genome Biol ; 25(1): 151, 2024 06 10.
Article en En | MEDLINE | ID: mdl-38858759
ABSTRACT
Deconvolution methods infer quantitative cell type estimates from bulk measurement of mixed samples including blood and tissue. DNA methylation sequencing measures multiple CpGs per read, but few existing deconvolution methods leverage this within-read information. We develop CelFiE-ISH, which extends an existing method (CelFiE) to use within-read haplotype information. CelFiE-ISH outperforms CelFiE and other existing methods, achieving 30% better accuracy and more sensitive detection of rare cell types. We also demonstrate the importance of marker selection and of tailoring markers for haplotype-aware methods. While here we use gold-standard short-read sequencing data, haplotype-aware methods will be well-suited for long-read sequencing.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Haplotipos / Metilación de ADN Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2024 Tipo del documento: Article País de afiliación: Israel

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Haplotipos / Metilación de ADN Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2024 Tipo del documento: Article País de afiliación: Israel