A dynamic model for genome-wide association studies

Kiranmoy Das, Jiahan Li, Zhong Wang, Chunfa Tong, Guifang Fu, Yao Li, Meng Xu, Kwangmi Ahn, David Mauger, Runze Li, Rongling Wu

Research output: Contribution to journalArticle

49 Citations (Scopus)

Abstract

Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.

Original languageEnglish (US)
Pages (from-to)629-639
Number of pages11
JournalHuman genetics
Volume129
Issue number6
DOIs
StatePublished - Jun 1 2011

Fingerprint

Genome-Wide Association Study
Genes

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

Cite this

Das, K., Li, J., Wang, Z., Tong, C., Fu, G., Li, Y., ... Wu, R. (2011). A dynamic model for genome-wide association studies. Human genetics, 129(6), 629-639. https://doi.org/10.1007/s00439-011-0960-6
Das, Kiranmoy ; Li, Jiahan ; Wang, Zhong ; Tong, Chunfa ; Fu, Guifang ; Li, Yao ; Xu, Meng ; Ahn, Kwangmi ; Mauger, David ; Li, Runze ; Wu, Rongling. / A dynamic model for genome-wide association studies. In: Human genetics. 2011 ; Vol. 129, No. 6. pp. 629-639.
@article{e99249bf2f2b4a64a23895c7b6fcdc1c,
title = "A dynamic model for genome-wide association studies",
abstract = "Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.",
author = "Kiranmoy Das and Jiahan Li and Zhong Wang and Chunfa Tong and Guifang Fu and Yao Li and Meng Xu and Kwangmi Ahn and David Mauger and Runze Li and Rongling Wu",
year = "2011",
month = "6",
day = "1",
doi = "10.1007/s00439-011-0960-6",
language = "English (US)",
volume = "129",
pages = "629--639",
journal = "Human Genetics",
issn = "0340-6717",
publisher = "Springer Verlag",
number = "6",

}

Das, K, Li, J, Wang, Z, Tong, C, Fu, G, Li, Y, Xu, M, Ahn, K, Mauger, D, Li, R & Wu, R 2011, 'A dynamic model for genome-wide association studies', Human genetics, vol. 129, no. 6, pp. 629-639. https://doi.org/10.1007/s00439-011-0960-6

A dynamic model for genome-wide association studies. / Das, Kiranmoy; Li, Jiahan; Wang, Zhong; Tong, Chunfa; Fu, Guifang; Li, Yao; Xu, Meng; Ahn, Kwangmi; Mauger, David; Li, Runze; Wu, Rongling.

In: Human genetics, Vol. 129, No. 6, 01.06.2011, p. 629-639.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A dynamic model for genome-wide association studies

AU - Das, Kiranmoy

AU - Li, Jiahan

AU - Wang, Zhong

AU - Tong, Chunfa

AU - Fu, Guifang

AU - Li, Yao

AU - Xu, Meng

AU - Ahn, Kwangmi

AU - Mauger, David

AU - Li, Runze

AU - Wu, Rongling

PY - 2011/6/1

Y1 - 2011/6/1

N2 - Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.

AB - Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.

UR - http://www.scopus.com/inward/record.url?scp=79959692796&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79959692796&partnerID=8YFLogxK

U2 - 10.1007/s00439-011-0960-6

DO - 10.1007/s00439-011-0960-6

M3 - Article

C2 - 21293879

AN - SCOPUS:79959692796

VL - 129

SP - 629

EP - 639

JO - Human Genetics

JF - Human Genetics

SN - 0340-6717

IS - 6

ER -

Das K, Li J, Wang Z, Tong C, Fu G, Li Y et al. A dynamic model for genome-wide association studies. Human genetics. 2011 Jun 1;129(6):629-639. https://doi.org/10.1007/s00439-011-0960-6