教師資料查詢 | 類別: 期刊論文 | 教師: 王彥雯 WANG, CHARLOTTE (瀏覽個人網頁)

標題:Re-examining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples
學年106
學期2
出版(發表)日期2018/05/01
作品名稱Re-examining Dis/Similarity-Based Tests for Rare-Variant Association with Case-Control Samples
作品名稱(其他語言)
著者Charlotte Wang; Jung-Ying Tzeng; Pei-Zhen Wu; Martin Preisig; Chuhsing Kate Hsiao
單位
出版者
著錄名稱、卷期、頁數GENETICS 209(1), p.105-113
摘要A properly designed distance-based measure can capture informative genetic differences among individuals with different phenotypes and can be used to detect variants responsible for the phenotypes. To detect associated variants, various tests have been designed to contrast genetic dissimilarity or similarity scores of certain subject groups in different ways, among which the most widely used strategy is to quantify the difference between the within-group genetic dissimilarity/similarity (i.e., case-case and control-control similarities) and the between-group dissimilarity/similarity (i.e., case-control similarities). While it has been noted that for common variants, the within-group and the between-group measures should all be included; in this work, we show that for rare variants, comparison based on the two within-group measures can more effectively quantify the genetic difference between cases and controls. The between-group measure tends to overlap with one of the two within-group measures for rare variants, although such overlap is not present for common variants. Consequently, a dissimilarity or similarity test that includes the between-group information tends to attenuate the association signals and leads to power loss. Based on these findings, we propose a dissimilarity test that compares the degree of SNP dissimilarity within cases to that within controls to better characterize the difference between two disease phenotypes. We provide the statistical properties, asymptotic distribution, and computation details for a small sample size of the proposed test. We use simulated and real sequence data to assess the performance of the proposed test, comparing it with other rare-variant methods including those similarity-based tests that use both within-group and between-group information. As similarity-based approaches serve as one of the dominating approaches in rare-variant analysis, our results provide some insight for the effective detection of rare variants.
關鍵字U-statistics;cross-sample comparison;within-sample comparison
語言英文(美國)
ISSN
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度
國別美國
公開徵稿
出版型式,電子版,紙本
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