Suppr超能文献

通过联合使用关联和连锁检验,并考虑上位性,来识别易感性基因。

Identifying susceptibility genes by using joint tests of association and linkage and accounting for epistasis.

机构信息

National Oceanic and Atmospheric Administration/National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, USA.

出版信息

BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S147. doi: 10.1186/1471-2156-6-S1-S147.

Abstract

Simulated Genetic Analysis Workshop 14 data were analyzed by jointly testing linkage and association and by accounting for epistasis using a candidate gene approach. Our group was unblinded to the "answers." The 48 single-nucleotide polymorphisms (SNPs) within the six disease loci were analyzed in addition to five SNPs from each of two non-disease-related loci. Affected sib-parent data was extracted from the first 10 replicates for populations Aipotu, Kaarangar, and Danacaa, and analyzed separately for each replicate. We developed a likelihood for testing association and/or linkage using data from affected sib pairs and their parents. Identical-by-descent (IBD) allele sharing between sibs was explicitly modeled using a conditional logistic regression approach and incorporating a covariate that represents expected IBD allele sharing given the genotypes of the sibs and their parents. Interactions were accounted for by performing likelihood ratio tests in stages determined by the highest order interaction term in the model. In the first stage, main effects were tested independently, and in subsequent stages, multilocus effects were tested conditional on significant marginal effects. A reduction in the number of tests performed was achieved by prescreening gene combinations with a goodness-of-fit chi square statistic that depended on mating-type frequencies. SNP-specific joint effects of linkage and association were identified for loci D1, D2, D3, and D4 in multiple replicates. The strongest effect was for SNP B03T3056, which had a median p-value of 1.98 x 10(-34). No two- or three-locus effects were found in more than one replicate.

摘要

采用候选基因方法,通过联合检验连锁与关联并考虑上位效应,对模拟遗传分析研讨会 14 数据进行了分析。我们小组对“答案”是知情的。除了来自两个非疾病相关基因座的每个基因座的 5 个 SNP 之外,还分析了这 6 个疾病基因座内的 48 个单核苷酸多态性(SNP)。从 Aipotu、Karaingar 和 Danacaa 三个群体的前 10 个重复中提取了受影响的同胞-父母数据,并分别对每个重复进行了分析。我们开发了一种使用受影响的同胞对及其父母的数据来检验关联和/或连锁的似然性。使用条件逻辑回归方法并结合一个协变量来明确模拟同胞之间的同源等位基因共享,该协变量表示根据同胞及其父母的基因型预期的同源等位基因共享。通过在模型中最高阶交互项确定的阶段进行似然比检验来考虑交互作用。在第一阶段,独立测试主要效应,在随后的阶段,在有显著边缘效应的条件下测试多基因座效应。通过依赖于交配型频率的拟合优度卡方统计来预筛选基因组合,从而减少了执行的测试数量。在多个重复中,确定了 D1、D2、D3 和 D4 基因座的 SNP 特异性连锁和关联的联合效应。最强的效应是 SNP B03T3056,其中位数 p 值为 1.98 x 10(-34)。在一个以上的重复中,没有发现两个或三个基因座的效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24a8/1866788/ba3424a35d0e/1471-2156-6-S1-S147-1.jpg

相似文献

1
Identifying susceptibility genes by using joint tests of association and linkage and accounting for epistasis.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S147. doi: 10.1186/1471-2156-6-S1-S147.
2
Searching for epistatic interactions in nuclear families using conditional linkage analysis.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S148. doi: 10.1186/1471-2156-6-S1-S148.
4
Testing association and linkage using affected-sib-parent study designs.
Genet Epidemiol. 2005 Nov;29(3):225-33. doi: 10.1002/gepi.20091.
5
Fine-mapping using the weighted average method for a case-control study.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S67. doi: 10.1186/1471-2156-6-S1-S67.
6
Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models.
PLoS One. 2016 Jan 11;11(1):e0146240. doi: 10.1371/journal.pone.0146240. eCollection 2016.
7
Mixture models for linkage analysis of affected sibling pairs and covariates.
Genet Epidemiol. 2002 Jan;22(1):52-65. doi: 10.1002/gepi.1043.
9
Linkage and association analyses of microsatellites and single-nucleotide polymorphisms in nuclear families.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S25. doi: 10.1186/1471-2156-6-S1-S25.

引用本文的文献

1
Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.
PLoS One. 2022 Feb 18;17(2):e0263390. doi: 10.1371/journal.pone.0263390. eCollection 2022.
2
Screening-testing approaches for gene-gene and gene-environment interactions using independent statistics.
Front Genet. 2013 Dec 30;4:306. doi: 10.3389/fgene.2013.00306. eCollection 2013.
3
A family-based association test to detect gene-gene interactions in the presence of linkage.
Eur J Hum Genet. 2012 Sep;20(9):973-80. doi: 10.1038/ejhg.2012.45. Epub 2012 Mar 14.
4
A fast algorithm for learning epistatic genomic relationships.
AMIA Annu Symp Proc. 2010 Nov 13;2010:341-5.
5
Identifying genetic interactions in genome-wide data using Bayesian networks.
Genet Epidemiol. 2010 Sep;34(6):575-81. doi: 10.1002/gepi.20514.

本文引用的文献

1
Testing association and linkage using affected-sib-parent study designs.
Genet Epidemiol. 2005 Nov;29(3):225-33. doi: 10.1002/gepi.20091.
3
Analysis of multilocus models of association.
Genet Epidemiol. 2003 Jul;25(1):36-47. doi: 10.1002/gepi.10237.
4
Association tests in nuclear families.
Hum Hered. 2001;52(2):66-76. doi: 10.1159/000053357.
5
Testing linkage disequilibrium in sibships.
Am J Hum Genet. 2000 Jul;67(1):244-8. doi: 10.1086/302973. Epub 2000 May 30.
7
Tests for linkage and association in nuclear families.
Am J Hum Genet. 1997 Aug;61(2):439-48. doi: 10.1086/514860.
8
General score tests for associations of genetic markers with disease using cases and their parents.
Genet Epidemiol. 1996;13(5):423-49. doi: 10.1002/(SICI)1098-2272(1996)13:5<423::AID-GEPI1>3.0.CO;2-3.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验