When there is uncertainty in sibling relationship,the classical affected sib-pair(ASP) linkage tests may be severely biased.This can happen,for example,if some of the half sib-pairs are mixed with full sib-pairs.The g...When there is uncertainty in sibling relationship,the classical affected sib-pair(ASP) linkage tests may be severely biased.This can happen,for example,if some of the half sib-pairs are mixed with full sib-pairs.The genomic control method has been used in association analysis to adjust for population structures.We show that the same idea can be applied to ASP linkage analysis with uncertainty in sibling relationship.Assuming that,in addition to the candidate marker,null markers that are unlinked to the disease locus are also genotyped,we may use the information on these loci to estimate the proportion of half sib-pairs and to correct for the bias and variance distortion caused by the heterogeneity of sibling relationship.Unlike in association studies,the null loci are not required to be matched with the candidate marker in allele frequency for ASP linkage analysis.This makes our approach flexible in selecting null markers.In our simulations,using a number of 30 or more null loci can effectively remove the bias and variance distortion.It is also shown that,even the null loci are weakly linked to the disease locus,the proposed method can also provide satisfactory correction.展开更多
Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be di...Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be discovered.Functional annotation of the genetic variants may increase the power of GWAS to identify disease genes,by providing prior information that can be used in Bayesian analysis or in reducing the number of tests.Expression quantitative trait loci（eQTLs） are genomic loci that regulate gene expression.Genetic mapping of eQTLs can help reveal novel functional effects of thousands of single nucleotide polymorphisms（SNPs）.The present review mainly focused on the current knowledge on brain eQTL mapping,and discussed some major methodological issues and their possible solutions.The frequently ignored problems of batch effects,covariates,and multiple testing were emphasized,since they can lead to false positives and false negatives.The future application of eQTL data in GWAS analysis was also discussed.展开更多
基金supported by National Natural Science Foundation of China(Grant No. 10971210)China Postdoctoral Science Foundation (Grant No. 20110490824)
文摘When there is uncertainty in sibling relationship,the classical affected sib-pair(ASP) linkage tests may be severely biased.This can happen,for example,if some of the half sib-pairs are mixed with full sib-pairs.The genomic control method has been used in association analysis to adjust for population structures.We show that the same idea can be applied to ASP linkage analysis with uncertainty in sibling relationship.Assuming that,in addition to the candidate marker,null markers that are unlinked to the disease locus are also genotyped,we may use the information on these loci to estimate the proportion of half sib-pairs and to correct for the bias and variance distortion caused by the heterogeneity of sibling relationship.Unlike in association studies,the null loci are not required to be matched with the candidate marker in allele frequency for ASP linkage analysis.This makes our approach flexible in selecting null markers.In our simulations,using a number of 30 or more null loci can effectively remove the bias and variance distortion.It is also shown that,even the null loci are weakly linked to the disease locus,the proposed method can also provide satisfactory correction.
文摘Genome-wide association study（GWAS） can be used to identify genes that increase the risk of psychiatric diseases.However,much of the disease heritability is still unexplained,suggesting that there are genes to be discovered.Functional annotation of the genetic variants may increase the power of GWAS to identify disease genes,by providing prior information that can be used in Bayesian analysis or in reducing the number of tests.Expression quantitative trait loci（eQTLs） are genomic loci that regulate gene expression.Genetic mapping of eQTLs can help reveal novel functional effects of thousands of single nucleotide polymorphisms（SNPs）.The present review mainly focused on the current knowledge on brain eQTL mapping,and discussed some major methodological issues and their possible solutions.The frequently ignored problems of batch effects,covariates,and multiple testing were emphasized,since they can lead to false positives and false negatives.The future application of eQTL data in GWAS analysis was also discussed.
