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本文引用的文献

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KEGG for linking genomes to life and the environment.京都基因与基因组百科全书,用于将基因组与生命及环境相联系。
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路径:一种促进基于通路的遗传关联分析的工具。

Path: a tool to facilitate pathway-based genetic association analysis.

机构信息

James Hogg iCAPTURE Center, University of British Columbia (UBC), Vancouver, BC, Canada.

出版信息

Bioinformatics. 2009 Sep 15;25(18):2444-6. doi: 10.1093/bioinformatics/btp431. Epub 2009 Jul 23.

DOI:10.1093/bioinformatics/btp431
PMID:19628508
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2735673/
Abstract

SUMMARY

Traditional methods of genetic study design and analysis work well under the scenario that a handful of single nucleotide polymorphisms (SNPs) independently contribute to the risk of disease. For complex diseases, susceptibility may be determined not by a single SNP, but rather a complex interplay between SNPs. For large studies involving hundreds of thousands of SNPs, a brute force search of all possible combinations of SNPs associated with disease is not only inefficient, but also results in a multiple testing paradigm, whereby larger and larger sample sizes are needed to maintain statistical power. Pathway-based methods are an example of one of the many approaches in identifying a subset of SNPs to test for interaction. To help determine which SNP-SNP interactions to test, we developed Path, a software application designed to help researchers interface their data with biological information from several bioinformatics resources. To this end, our application brings together currently available information from nine online bioinformatics resources including the National Center for Biotechnology Information (NCBI), Online Mendelian Inheritance in Man (OMIM), Kyoto Encyclopedia of Genes and Genomes (KEGG), UCSC Genome Browser, Seattle SNPs, PharmGKB, Genetic Association Database, the Single Nucleotide Polymorphism database (dbSNP) and the Innate Immune Database (IIDB).

AVAILABILITY

The software, example datasets and tutorials are freely available from http://genapha.icapture.ubc.ca/PathTutorial.

摘要

摘要

传统的遗传研究设计和分析方法在少数单核苷酸多态性 (SNP) 独立影响疾病风险的情况下效果很好。对于复杂疾病,易感性可能不是由单个 SNP 决定,而是由 SNP 之间的复杂相互作用决定。对于涉及数十万 SNP 的大型研究,对与疾病相关的所有 SNP 组合进行穷举搜索不仅效率低下,而且还会导致多重检验范式,需要更大的样本量来维持统计功效。基于途径的方法是识别要测试的 SNP 相互作用的子集的众多方法之一。为了帮助确定要测试的 SNP-SNP 相互作用,我们开发了 Path,这是一款软件应用程序,旨在帮助研究人员将他们的数据与来自几个生物信息学资源的生物信息进行接口。为此,我们的应用程序汇集了来自九个在线生物信息学资源的现有信息,包括国家生物技术信息中心 (NCBI)、在线孟德尔遗传在人 (OMIM)、京都基因与基因组百科全书 (KEGG)、UCSC 基因组浏览器、西雅图 SNPs、PharmGKB、遗传关联数据库、单核苷酸多态性数据库 (dbSNP) 和先天免疫数据库 (IIDB)。

可用性

软件、示例数据集和教程可从 http://genapha.icapture.ubc.ca/PathTutorial 免费获得。