Disease category-specific annotation of variants using an ensemble learning framework

doi:10.1093/bib/bbab438

CSpace > 应用数学研究所

	Disease category-specific annotation of variants using an ensemble learning framework
	Cao, Zhen1,2 ; Huang, Yanting 3; Duan, Ran 4; Jin, Peng 5; Qin, Zhaohui S.6; Zhang, Shihua1
	2022-01-17
发表期刊	BRIEFINGS IN BIOINFORMATICS
ISSN	1467-5463
卷号	23 期号:1 页码:15
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.
关键词	complex disease disease category functional annotation non-coding variant ensemble learning
DOI	10.1093/bib/bbab438
收录类别	SCI
语种	英语
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
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:000763000800083
出版者	OXFORD UNIV PRESS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/60289
专题	应用数学研究所
通讯作者	Qin, Zhaohui S.; Zhang, Shihua
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Alibaba Hlth Informat Technol Ltd, Beijing, Peoples R China 3.Emory Univ, Dept Comp Sci, Atlanta, GA 30322 USA 4.Yunnan Univ, Dept Software Engn, Kunming, Yunnan, Peoples R China 5.Emory Univ, Dept Human Genet, Sch Med, Atlanta, GA 30322 USA 6.Emory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA
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.