Genetic analysis of biological pathway data through genomic randomization

Brian L. Yaspan, William S. Bush, Eric S. Torstenson, Deqiong Ma, Margaret A. Pericak-Vance, Marylyn Deriggi Ritchie, James S. Sutcliffe, Jonathan L. Haines

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Abstract

Genome Wide Association Studies (GWAS) are a standard approach for large-scale common variation characterization and for identification of single loci predisposing to disease. However, due to issues of moderate sample sizes and particularly multiple testing correction, many variants of smaller effect size are not detected within a single allele analysis framework. Thus, small main effects and potential epistatic effects are not consistently observed in GWAS using standard analytical approaches that consider only single SNP alleles. Here, we propose unique methodology that aggregates variants of interest (for example, genes in a biological pathway) using GWAS results. Multiple testing and type I error concerns are minimized using empirical genomic randomization to estimate significance. Randomization corrects for common pathway-based analysis biases, such as SNP coverage and density, linkage disequilibrium, gene size and pathway size. Pathway Analysis by Randomization Incorporating Structure (PARIS) applies this randomization and in doing so directly accounts for linkage disequilibrium effects. PARIS is independent of association analysis method and is thus applicable to GWAS datasets of all study designs. Using the KEGG database as an example, we apply PARIS to the publicly available Autism Genetic Resource Exchange GWAS dataset, revealing pathways with a significant enrichment of positive association results.

Original languageEnglish (US)
Pages (from-to)563-571
Number of pages9
JournalHuman genetics
Volume129
Issue number5
DOIs
StatePublished - May 1 2011

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Random Allocation
Genome-Wide Association Study
Linkage Disequilibrium
Single Nucleotide Polymorphism
Alleles
Autistic Disorder
Sample Size
Genes
Databases

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

Cite this

Yaspan, B. L., Bush, W. S., Torstenson, E. S., Ma, D., Pericak-Vance, M. A., Ritchie, M. D., ... Haines, J. L. (2011). Genetic analysis of biological pathway data through genomic randomization. Human genetics, 129(5), 563-571. https://doi.org/10.1007/s00439-011-0956-2
Yaspan, Brian L. ; Bush, William S. ; Torstenson, Eric S. ; Ma, Deqiong ; Pericak-Vance, Margaret A. ; Ritchie, Marylyn Deriggi ; Sutcliffe, James S. ; Haines, Jonathan L. / Genetic analysis of biological pathway data through genomic randomization. In: Human genetics. 2011 ; Vol. 129, No. 5. pp. 563-571.
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Yaspan, BL, Bush, WS, Torstenson, ES, Ma, D, Pericak-Vance, MA, Ritchie, MD, Sutcliffe, JS & Haines, JL 2011, 'Genetic analysis of biological pathway data through genomic randomization', Human genetics, vol. 129, no. 5, pp. 563-571. https://doi.org/10.1007/s00439-011-0956-2

Genetic analysis of biological pathway data through genomic randomization. / Yaspan, Brian L.; Bush, William S.; Torstenson, Eric S.; Ma, Deqiong; Pericak-Vance, Margaret A.; Ritchie, Marylyn Deriggi; Sutcliffe, James S.; Haines, Jonathan L.

In: Human genetics, Vol. 129, No. 5, 01.05.2011, p. 563-571.

Research output: Contribution to journalArticle

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Yaspan BL, Bush WS, Torstenson ES, Ma D, Pericak-Vance MA, Ritchie MD et al. Genetic analysis of biological pathway data through genomic randomization. Human genetics. 2011 May 1;129(5):563-571. https://doi.org/10.1007/s00439-011-0956-2