The PPLD has advantages over conventional regression methods in application to moderately sized genome-wide association studies.
The PPLD has advantages over conventional regression methods in application to moderately sized genome-wide association studies.
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DOI:
10.1371/journal.pone.0257164
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发表时间:
2021
期刊:
影响因子:
3.7
通讯作者:
Seok SC
中科院分区:
文献类型:
--
作者:
Vieland VJ;Seok SC
In earlier work, we have developed and evaluated an alternative approach to the analysis of GWAS data, based on a statistic called the PPLD. More recently, motivated by a GWAS for genetic modifiers of the X-linked Mendelian disorder Duchenne Muscular Dystrophy (DMD), we adapted the PPLD for application to time-to-event (TE) phenotypes. Because DMD itself is relatively rare, this is a setting in which the very large sample sizes generally assembled for GWAS are simply not attainable. For this reason, statistical methods specially adapted for use in small data sets are required. Here we explore the behavior of the TE-PPLD via simulations, comparing the TE-PPLD with Cox Proportional Hazards analysis in the context of small to moderate sample sizes. Our results will help to inform our approach to the DMD study going forward, and they illustrate several respects in which the TE-PPLD, and by extension the original PPLD, offer advantages over regression-based approaches to GWAS in this context.
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