用于基因发现的外显子组的计算机分析。

In silico analysis of the exome for gene discovery.

作者信息

Hinchcliffe Marcus, Webster Paul

机构信息

Department of Molecular and Clinical Genetics, Royal Prince Alfred Hospital, The University of Sydney, Camperdown, NSW, Australia.

出版信息

Methods Mol Biol. 2011;760:109-28. doi: 10.1007/978-1-61779-176-5_7.

DOI:10.1007/978-1-61779-176-5_7

PMID:21779993

Abstract

Here we describe a bioinformatic strategy for extracting and analyzing the list of variants revealed from an exome sequencing project to identify potential disease genes. This in silico method filters out the majority of common SNPs and extracts a list of potential candidate protein-coding and non-coding RNA (ncRNA) genes. The workflow employs Galaxy, a publically available Web-based software, to filter and sort sequence variants identified by capture-based target enrichment and sequencing from exomes including selected ncRNAs.

摘要

在此，我们描述了一种生物信息学策略，用于提取和分析外显子组测序项目中揭示的变异列表，以识别潜在的疾病基因。这种计算机方法滤除了大多数常见的单核苷酸多态性（SNP），并提取了一份潜在的候选蛋白质编码和非编码RNA（ncRNA）基因列表。该工作流程采用Galaxy（一种基于网络的公开可用软件）来过滤和分类通过基于捕获的目标富集和外显子组测序（包括选定的ncRNA）鉴定出的序列变异。