{"title":"Understanding the Population Structure Correction Regression","authors":"T. T. Mai, Pierre Alquier","doi":"10.11159/icsta22.114","DOIUrl":"https://doi.org/10.11159/icsta22.114","url":null,"abstract":"Although genome-wide association studies (GWAS) on complex traits have achieved great successes, the current leading GWAS approaches simply perform to test each genotype-phenotype association separately for each genetic variant. Curiously, the statistical properties for using these approaches is not known when a joint model for the whole genetic variants is considered. Here we advance in GWAS in understanding the statistical properties of the\"population structure correction\"(PSC) approach, a standard univariate approach in GWAS. We further propose and analyse a correction to the PSC approach, termed as\"corrected population correction\"(CPC). Together with the theoretical results, numerical simulations show that CPC is always comparable or better than PSC, with a dramatic improvement in some special cases.","PeriodicalId":325859,"journal":{"name":"Proceedings of the 4th International Conference on Statistics: Theory and Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125594768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}