A comparison study on multivariate methods for joint-SNVs association analysis
Refereed conference paper presented and published in conference proceedings

香港中文大學研究人員
替代計量分析
.

其它資訊
摘要Single nucleotide variants (SNVs) have been discovered that they play crucial roles in disease pathogenesis as genetic factors. Featured by analyzing multiple SNVs in a biological module (e.g. exon, gene, etc.) collectively, the joint-SNVs studies are increasingly attractive in genome-wide association studies (GWASs), for which extensive efforts have been devoted to pursue effective multivariate methods. In this paper, we first reviewed several main streams of existing methods and their limitations in joint-SNVs studies. Then, we introduced a recently proposed novel method, namely statistic-space boundary based test (S-space BBT) to tackle these limitations. Via computational experiments on simulation datasets, not only we figured out the applicable scenarios for the six methods in considering the effect direction and whether the single significant is involved in, but also demonstrated the strong detecting sensitivity of S-space BBT under the different conditions of odds ratio, minor allele frequency, and the linkage disequilibrium. We anticipate that our study may provide clues for multivariate method selection, and that S-space BBT may play a promising role in the joint-SNVs analysis.
著者Jin-Xiong Lv, Han-Chen Huang, Run-Sheng Chen, Lei Xu
會議名稱Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on
會議開始日15.12.2016
會議完結日18.12.2016
會議地點Shenzhen
會議國家/地區中國
期刊名稱Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on
會議論文集題名Bioinformatics and Biomedicine (BIBM), 2016 IEEE International Conference on
出版年份2016
月份12
出版社IEEE
頁次1771 - 1776
國際標準書號978-1-5090-1612-9
電子國際標準書號978-1-5090-1611-2
語言美式英語
關鍵詞Genomics, Bioinformatics, Manganese

上次更新時間 2021-13-09 於 00:21