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
DOI10.1093/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.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace