Challenges and directions: an analysis of Genetic Analysis Workshop 17 data by collapsing rare variants within family data
详细信息    查看全文
  • 作者:Peng Lin (1)
    Michael Hamm (1)
    Sarah Hartz (1)
    Zhehao Zhang (1)
    John P Rice (1)
  • 刊名:BMC Proceedings
  • 出版年:2011
  • 出版时间:December 2011
  • 年:2011
  • 卷:5
  • 期:9-supp
  • 全文大小:181KB
  • 参考文献:1. Manolio TA: Genomewide association studies and assessment of the risk of disease. / New Engl J Med 2010, 363:166-76. CrossRef
    2. Dering C, Pugh E, Ziegler A: Statistical analysis of rare sequence variants: an overview of collapsing methods. / Genet Epidemiol 2011,X(suppl X):X-X.
    3. Li B, Leal SM: Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. / Am J Hum Genet 2008, 83:311-21. CrossRef
    4. Thornton T, McPeek MS: Case-control association testing with related individuals: a more powerful quasi-likelihood score test. / Am J Hum Genet 2007, 81:321-37. CrossRef
    5. Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, et al.: A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. / Nat Genet 2006, 38:203-08. CrossRef
    6. Bourgain C, Hoffjan S, Nicolae R, Newman D, Steiner L, Walker K, Reynolds R, Ober C, McPeek MS: Novel case-control test in a founder population identifies P-selectin as an atopy-susceptibility locus. / Am J Hum Genet 2003, 73:612-26. CrossRef
    7. Doull IJ: Recent advances in cystic fibrosis. / Arch Dis Child 2001, 85:62-6. CrossRef
    8. Ng PC, Henikoff S: SIFT: Predicting amino acid changes that affect protein function. / Nucleic Acids Res 2003, 31:3812-814. CrossRef
    9. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR: A method and server for predicting damaging missense mutations. / Nat Meth 2010, 7:248-49. CrossRef
    10. Guey LT, Kravic J, Melander O, Burtt NP, Laramie JM, Lyssenko V, Jonsson A, Lindholm E, Tuomi T, Isomaa B, / et al.: Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants. / Genet Epidemiol 2011,X(suppl X):X-X.
  • 作者单位:Peng Lin (1)
    Michael Hamm (1)
    Sarah Hartz (1)
    Zhehao Zhang (1)
    John P Rice (1)

    1. Department of Psychiatry, Washington University, 660 S. Euclid Ave., Campus Box 8134, St. Louis, MO, 63110, USA
文摘
Recent studies suggest that the traditional case-control study design does not have sufficient power to discover rare risk variants. Two different methods—collapsing and family data—are suggested as alternatives for discovering these rare variants. Compared with common variants, rare variants have unique characteristics. In this paper, we assess the distribution of rare variants in family data. We notice that a large number of rare variants exist only in one or two families and that the association result is largely shaped by those families. Therefore we explore the possibility of integrating both the collapsing method and the family data method. This combinational approach offers a potential power boost for certain causal genes, including VEGFA, VEGFC, SIRT1, SREBF1, PIK3R3, VLDLR, PLAT, and FLT4, and thus deserves further investigation.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700