BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference.

Rahmani, Elior; Schweiger, Regev; Shenhav, Liat; Wingert, Theodora; Hofer, Ira; Gabel, Eilon; Eskin, Eleazar; Halperin, Eran

Rahmani, Elior; Schweiger, Regev; Shenhav, Liat; Wingert, Theodora; Hofer, Ira; Gabel, Eilon; Eskin, Eleazar; Halperin, Eran.

Afiliação

Rahmani E; Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
Schweiger R; Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
Shenhav L; Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
Wingert T; Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Hofer I; Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Gabel E; Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Eskin E; Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
Halperin E; Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA.

Genome Biol ; 19(1): 141, 2018 09 21.

Article em En | MEDLINE | ID: mdl-30241486

Assuntos

Contagem de Células/métodos; Metilação de DNA; Teorema de Bayes

Palavras-chave

Bayesian model; Cell counts; Cell-type composition; DNA methylation; Epigenetics; Epigenome-wide association studies; Tissue heterogeneity

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Contagem de Células / Metilação de DNA Tipo de estudo: Prognostic_studies Idioma: En Revista: Genome Biol Assunto da revista: BIOLOGIA MOLECULAR / GENETICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

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