Data validation and statistical issues such as power and other considerations in genome-wide association study (GWAS)

被引:0
|
作者
Tomita, Makoto [1 ]
机构
[1] Yokohama City Univ, Yokohama, Kanagawa, Japan
关键词
data quality control; genome-wide association study; GWAS; p-value QQ-plot; statistical power; HAPLOTYPE BLOCKS; LD;
D O I
10.1002/wics.1601
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A series of steps in genomic data analysis will be presented. In data validation, starting with marker quality control, he mentioned structuring problems from ethnic populations, genome-wide significant levels, Manhattan plots, and Haploview. Statistical issues such as power, sample size calculation, false discovery rate, and QQ plot of p-values were also introduced. This article is categorized under: Applications of Computational Statistics > DNA Analysis
引用
收藏
页数:12
相关论文
共 50 条
  • [31] An Introduction to Genome-Wide Association Studies: GWAS for Dummies
    Uitterlinden, A. G.
    SEMINARS IN REPRODUCTIVE MEDICINE, 2016, 34 (04) : 196 - 204
  • [32] Editorial: Statistical methods for genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) and their applications
    Shao, Mengting
    Zhang, Zilong
    Sun, Huiyan
    He, Jingni
    Wang, Juexin
    Zhang, Qingrun
    Cao, Chen
    FRONTIERS IN GENETICS, 2023, 14
  • [33] Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure
    Teo, Yik Y.
    CURRENT OPINION IN LIPIDOLOGY, 2008, 19 (02) : 133 - 143
  • [34] Impact of the Tagging on the Statistical Power of Association Tests in Genome-Wide Association Studies
    Emily, M.
    HUMAN HEREDITY, 2015, 79 (01) : 34 - 34
  • [35] In silico drug discovery for Parkinson's disease by using genome-wide association study (GWAS) data
    Uenaka, T.
    Satake, W.
    Chieng, C. P.
    Okada, Y.
    Toda, T.
    MOVEMENT DISORDERS, 2015, 30 : S51 - S51
  • [36] GWAS Analyzer: integrating genotype, phenotype and public annotation data for genome-wide association study analysis
    Fong, Christine
    Ko, Dennis C.
    Wasnick, Michael
    Radey, Matthew
    Miller, Samuel I.
    Brittnacher, Mitchell
    BIOINFORMATICS, 2010, 26 (04) : 560 - 564
  • [37] Predicting allergic diseases in children using genome-wide association study (GWAS) data and family history
    Park, Jaehyun
    Jang, Haerin
    Kim, Mina
    Hong, Jung Yeon
    Kim, Yoon Hee
    Sohn, Myung Hyun
    Park, Sang-Cheol
    Won, Sungho
    Kim, Kyung Won
    WORLD ALLERGY ORGANIZATION JOURNAL, 2021, 14 (05):
  • [38] Using Repeated Measures to Improve the Precision and Power of Genome-Wide Association Studies (GWAS)
    Kwong, Alex S. F.
    Adams, Mark J.
    Grimes, Poppy Z.
    Morries, Tim T.
    Griffith, Gareth
    Eley, Thalia C.
    Tilling, Kate
    McIntosh, Andrew
    BEHAVIOR GENETICS, 2024, 54 (06) : 576 - 577
  • [39] Genome-wide association study (GWAS), quantitative trait analyses and population structure
    Yoo, Hee Jeong
    EUROPEAN CHILD & ADOLESCENT PSYCHIATRY, 2011, 20 (01) : S80 - S80
  • [40] Effect of case and control definitions on genome-wide association study (GWAS) findings
    Isgut, Monica
    Song, Kijoung
    Ehm, Margaret G.
    Wang, May Dongmei
    Davitte, Jonathan
    GENETIC EPIDEMIOLOGY, 2023, 47 (05) : 394 - 406