Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments.

Deng, Chao; Daley, Timothy; Calabrese, Peter; Ren, Jie; Smith, Andrew D

Deng, Chao; Daley, Timothy; Calabrese, Peter; Ren, Jie; Smith, Andrew D.

Afiliação

Deng C; Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.
Daley T; Departments of Statistics and Bioengineering, Stanford University, Stanford, California, USA.
Calabrese P; Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.
Ren J; Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.
Smith AD; Quantitative and Computational Biology, University of Southern California, Los Angeles, California, USA.

J Comput Biol ; 27(7): 1130-1143, 2020 07.

Article em En | MEDLINE | ID: mdl-31725321

Assuntos

Sequenciamento de Nucleotídeos em Larga Escala/métodos; Modelos Genéticos; Algoritmos; Genoma; Análise de Célula Única; Sequenciamento Completo do Genoma/métodos

Palavras-chave

Padé approximant; genome coverage; mixture of Poisson distributions; nonparametric; single-cell whole-genome sequencing; species accumulation curve

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google