Disease category-specific annotation of variants using an ensemble learning framework | |
Cao, Zhen5,6; Huang, Yanting4; Duan, Ran3; Jin, Peng2; Qin, Zhaohui S.1; Zhang, Shihua6 | |
刊名 | BRIEFINGS IN BIOINFORMATICS |
2022-01-17 | |
卷号 | 23期号:1页码:15 |
关键词 | complex disease disease category functional annotation non-coding variant ensemble learning |
ISSN号 | 1467-5463 |
DOI | 10.1093/bib/bbab438 |
英文摘要 | Understanding the impact of non-coding sequence variants on complex diseases is an essential problem. We present a novel ensemble learning framework-CASAVA, to predict genomic loci in terms of disease category-specific risk. Using disease-associated variants identified by GWAS as training data, and diverse sequencing-based genomics and epigenomics profiles as features, CASAVA provides risk prediction of 24 major categories of diseases throughout the human genome. Our studies showed that CASAVA scores at a genomic locus provide a reasonable prediction of the disease-specific and disease category-specific risk prediction for non-coding variants located within the locus. Taking MHC2TA and immune system diseases as an example, we demonstrate the potential of CASAVA in revealing variant-disease associations. A website (http://zhanglabtools.org/CASAVA) has been built to facilitate easily access to CASAVA scores. |
资助项目 | National Key R&D Program of China[2019YFA0709501] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDPB17] ; Key-Area Research and Development of Guangdong Province[2020B1111190001] ; National Ten Thousand Talent Program for Young Top-notch Talents ; CAS Frontier Science Research Key Project for Top Young Scientist[QYZDB-SSW-SYS008] ; National Natural Science Foundation of China[61621003] |
WOS研究方向 | Biochemistry & Molecular Biology ; Mathematical & Computational Biology |
语种 | 英语 |
出版者 | OXFORD UNIV PRESS |
WOS记录号 | WOS:000763000800083 |
内容类型 | 期刊论文 |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/60288] |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Qin, Zhaohui S.; Zhang, Shihua |
作者单位 | 1.Emory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA 2.Emory Univ, Dept Human Genet, Sch Med, Atlanta, GA 30322 USA 3.Yunnan Univ, Dept Software Engn, Kunming, Yunnan, Peoples R China 4.Emory Univ, Dept Comp Sci, Atlanta, GA 30322 USA 5.Alibaba Hlth Informat Technol Ltd, Beijing, Peoples R China 6.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Cao, Zhen,Huang, Yanting,Duan, Ran,et al. Disease category-specific annotation of variants using an ensemble learning framework[J]. BRIEFINGS IN BIOINFORMATICS,2022,23(1):15. |
APA | Cao, Zhen,Huang, Yanting,Duan, Ran,Jin, Peng,Qin, Zhaohui S.,&Zhang, Shihua.(2022).Disease category-specific annotation of variants using an ensemble learning framework.BRIEFINGS IN BIOINFORMATICS,23(1),15. |
MLA | Cao, Zhen,et al."Disease category-specific annotation of variants using an ensemble learning framework".BRIEFINGS IN BIOINFORMATICS 23.1(2022):15. |
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