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Methods for copy number aberration detection from single-cell DNA-sequencing data.
Mallory, Xian F; Edrisi, Mohammadamin; Navin, Nicholas; Nakhleh, Luay.
Afiliación
  • Mallory XF; Department of Computer Science, Rice University, Houston, TX, USA.
  • Edrisi M; Department of Computer Science, Florida State University, Tallahassee, FL, USA.
  • Navin N; Department of Computer Science, Rice University, Houston, TX, USA.
  • Nakhleh L; Department of Genetics, the University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
Genome Biol ; 21(1): 208, 2020 08 17.
Article en En | MEDLINE | ID: mdl-32807205
ABSTRACT
Copy number aberrations (CNAs), which are pathogenic copy number variations (CNVs), play an important role in the initiation and progression of cancer. Single-cell DNA-sequencing (scDNAseq) technologies produce data that is ideal for inferring CNAs. In this review, we review eight methods that have been developed for detecting CNAs in scDNAseq data, and categorize them according to the steps of a seven-step pipeline that they employ. Furthermore, we review models and methods for evolutionary analyses of CNAs from scDNAseq data and highlight advances and future research directions for computational methods for CNA detection from scDNAseq data.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Secuencia de Bases / Análisis de Secuencia de ADN / Biología Computacional / Variaciones en el Número de Copia de ADN Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Secuencia de Bases / Análisis de Secuencia de ADN / Biología Computacional / Variaciones en el Número de Copia de ADN Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos