SeqSQC: A Bioconductor Package for Evaluating the Sample Quality of Next-generation Sequencing Data / 基因组蛋白质组与生物信息学报·英文版
Genomics, Proteomics & Bioinformatics
;
(4): 211-218, 2019.
Artigo
em Inglês
| WPRIM
| ID: wpr-772957
ABSTRACT
As next-generation sequencing (NGS) technology has become widely used to identify genetic causal variants for various diseases and traits, a number of packages for checking NGS data quality have sprung up in public domains. In addition to the quality of sequencing data, sample quality issues, such as gender mismatch, abnormal inbreeding coefficient, cryptic relatedness, and population outliers, can also have fundamental impact on downstream analysis. However, there is a lack of tools specialized in identifying problematic samples from NGS data, often due to the limitation of sample size and variant counts. We developed SeqSQC, a Bioconductor package, to automate and accelerate sample cleaning in NGS data of any scale. SeqSQC is designed for efficient data storage and access, and equipped with interactive plots for intuitive data visualization to expedite the identification of problematic samples. SeqSQC is available at http//bioconductor.org/packages/SeqSQC.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Padrões de Referência
/
Software
/
Neoplasias da Mama
/
Genoma Humano
/
Estudos de Coortes
/
Grupos Raciais
/
Sequenciamento de Nucleotídeos em Larga Escala
/
Sequenciamento do Exoma
/
Genética
/
Métodos
Tipo de estudo:
Estudo de etiologia
/
Estudo de incidência
/
Estudo observacional
/
Estudo prognóstico
/
Fatores de risco
Limite:
Feminino
/
Humanos
Idioma:
Inglês
Revista:
Genomics, Proteomics & Bioinformatics
Ano de publicação:
2019
Tipo de documento:
Artigo
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