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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
A reanalysis of a genome-wide association study on breast cancer in Asian populations using the SG10K_Health
Xuling Chang1,2,3, Shivaani Mariapun4, Mengyu Li5
1Department of Infectious Diseases, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, 792 Elizabeth St, Melbourne VIC 3000, Australia.
Abstract:
Genome-wide association studies (GWAS) have identified numerous genetic variants linked to breast cancer risk, but most discoveries come from European populations, limiting their applicability to other populations. Here, we show that the choice of genotype imputation reference panel, an essential step for GWAS, affects variant detection in Asian populations. Using two large breast cancer datasets from the Breast Cancer Association Consortium (n = 38 954 Asian samples), we compared the 1000 Genomes (1KG) reference panel with SG10K_Health (SG10K), an Asian-specific panel. SG10K imputed more rare variants and achieved higher accuracy for rare alleles (MAF < 0.001), while 1KG performed better for common variants in some contexts. Differences in panel performance influenced association signals, including breast cancer candidate loci such as FGFR2, TOX3, and ESR1. Together, these findings support the use of population-specific imputation panels as a means to improve variant discovery in underrepresented populations.
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