A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data
Genomics & Informatics
;
: 191-199, 2013.
Artigo
em Inglês
| WPRIM
| ID: wpr-11255
ABSTRACT
High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Genoma Humano
/
Estatística como Assunto
/
Alinhamento de Sequência
/
Genoma
/
Sequenciamento de Nucleotídeos em Larga Escala
Limite:
Humanos
Idioma:
Inglês
Revista:
Genomics & Informatics
Ano de publicação:
2013
Tipo de documento:
Artigo
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