WEN-CHUNG LEEShu Y.-H.2020-11-192020-11-1920040001-8244https://www.scopus.com/inward/record.uri?eid=2-s2.0-4444308753&doi=10.1023%2fB%3aBEGE.0000038490.06697.cb&partnerID=40&md5=087a8169f55554e886209a239c8a4c3chttps://scholars.lib.ntu.edu.tw/handle/123456789/521824Family-based association approach for mapping disease-susceptibility genes of complex human diseases is a topical issue in genetic epidemiology. It is well known that admixture between genetically differentiated populations can result in high levels of linkage disequilibrium at loci separated far apart. This property has been capitalized upon to reduce the burden of genotyping in a genomewide association scan. The authors describe a new approach for admixture mapping - the "interval principal component test" (IPCT). The genome is divided into a multitude of non-overlapping "intervals" (with interval length of 10-20 cM) and the information of the markers in the same interval is integrated using the principal component analysis. Monte-Carlo simulation shows that an interval-by-interval scan using IPCT has much better performances than a conventional marker-by-marker scan using the transmission/disequilibrium test (TDT).English[SDGs]SDG3article; disease predisposition; family; gene locus; gene mapping; genetic epidemiology; genetic linkage; genetic susceptibility; genetic variability; genome analysis; genotype; human; Monte Carlo method; population; Computer Simulation; Disease Susceptibility; Genetic Markers; Genetics, Medical; Humans; Models, Genetic; Monte Carlo Methodjournal article10.1023/B:BEGE.0000038490.06697.cb153195752-s2.0-4444308753