國家衛生研究院 NHRI:Item 3990099045/12950
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 12145/12927 (94%)
造访人次 : 853712      在线人数 : 1156
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    主页 ‧ 登入 ‧ 上传 ‧ 说明 ‧ 关于NHRI ‧ 管理 到手机版


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.nhri.org.tw/handle/3990099045/12950


    题名: Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale
    作者: Li, XH;Li, ZL;Zhou, HF;Gaynor, SM;Liu, YW;Chen, H;Sun, R;Dey, R;Arnett, DK;Aslibekyan, S;Ballantyne, CM;Bielak, LF;Blangero, J;Boerwinkle, E;Bowden, DW;Broome, JG;Conomos, MP;Correa, A;Cupples, LA;Curran, JE;Freedman, BI;Guo, XQ;Hindy, G;Irvin, MR;Kardia, SLR;Kathiresan, S;Khan, AT;Kooperberg, CL;Laurie, CC;Liu, XS;Mahaney, MC;Manichaikul, AW;Martin, LW;Mathias, RA;McGarvey, ST;Mitchell, BD;Montasser, ME;Moore, JE;Morrison, AC;O'Connell, JR;Palmer, ND;Pampana, A;Peralta, JM;Peyser, PA;Psaty, BM;Redline, S;Rice, KM;Rich, SS;Smith, JA;Tiwari, HK;Tsai, MCY;Vasan, RS;Wang, FF;Weeks, DE;Weng, ZP;Wilson, JG;Yanek, LR;Abe, N;Abe, N;Abecasis, GR;Aguet, F;Albert, C;Almasy, L;Alonso, A;Ament, S;Anderson, P;Anugu, P;Applebaum-Bowden, D;Ardlie, K;Arking, D;Arnett, DK;Ashley-Koch, A;Aslibekyan, S;Assimes, T;Auer, P;Avramopoulos, D;Barnard, J;Barnes, K;Barr, RG;Barron-Casella, E;Barwick, L;Beaty, T;Beck, G;Becker, D;Becker, L;Beer, R;Beitelshees, A;Benjamin, E;Benos, T;Bezerra, M;Bielak, LF;Bis, J;Blackwell, T;Blangero, J;Boerwinkle, E;Bowden, DW;Bowler, R;Brody, J;Broeckel, U;Broome, JG, et al.
    贡献者: Institute of Population Health Sciences;National Institute of Cancer Research
    摘要: Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs ofNPC1L1and an intergenic region nearAPOC1P1associated with low-density lipoprotein cholesterol. STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.
    日期: 2020-09
    關聯: Nature Genetics. 2020 Sep;52(9):969-983.
    Link to: http://dx.doi.org/10.1038/s41588-020-0676-4
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1061-4036&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000562341800001
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85089736482
    显示于类别:[Ren-Hua Chung] Periodical Articles
    [Chao A. Hsiung] Periodical Articles
    [I-Shou Chang] Periodical Articles

    文件中的档案:

    档案 描述 大小格式浏览次数
    ISI000562341800001.pdf3016KbAdobe PDF405检视/开启


    在NHRI中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈