↓ Skip to main content

PLOS

SNP-SNP Interactions Discovered by Logic Regression Explain Crohn's Disease Genetics

Overview of attention for article published in PLOS ONE, October 2012
Altmetric Badge

Mentioned by

blogs
1 blog
twitter
7 X users

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
82 Mendeley
citeulike
2 CiteULike
Title
SNP-SNP Interactions Discovered by Logic Regression Explain Crohn's Disease Genetics
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0043035
Pubmed ID
Authors

Irina Dinu, Surakameth Mahasirimongkol, Qi Liu, Hideki Yanai, Noha Sharaf Eldin, Erin Kreiter, Xuan Wu, Shahab Jabbari, Katsushi Tokunaga, Yutaka Yasui

Abstract

In genome-wide association studies (GWAS), the association between each single nucleotide polymorphism (SNP) and a phenotype is assessed statistically. To further explore genetic associations in GWAS, we considered two specific forms of biologically plausible SNP-SNP interactions, 'SNP intersection' and 'SNP union,' and analyzed the Crohn's Disease (CD) GWAS data of the Wellcome Trust Case Control Consortium for these interactions using a limited form of logic regression. We found strong evidence of CD-association for 195 genes, identifying novel susceptibility genes (e.g., ISX, SLCO6A1, TMEM183A) as well as confirming many previously identified susceptibility genes in CD GWAS (e.g., IL23R, NOD2, CYLD, NKX2-3, IL12RB2, ATG16L1). Notably, 37 of the 59 chromosomal locations indicated for CD-association by a meta-analysis of CD GWAS, involving over 22,000 cases and 29,000 controls, were represented in the 195 genes, as well as some chromosomal locations previously indicated only in linkage studies, but not in GWAS. We repeated the analysis with two smaller GWASs from the Database of Genotype and Phenotype (dbGaP): in spite of differences of populations and study power across the three datasets, we observed some consistencies across the three datasets. Notable examples included TMEM183A and SLCO6A1 which exhibited strong evidence consistently in our WTCCC and both of the dbGaP SNP-SNP interaction analyses. Examining these specific forms of SNP interactions could identify additional genetic associations from GWAS. R codes, data examples, and a ReadMe file are available for download from our website: http://www.ualberta.ca/~yyasui/homepage.html.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 5%
United Kingdom 1 1%
Germany 1 1%
Unknown 76 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 28%
Student > Ph. D. Student 21 26%
Student > Master 7 9%
Student > Bachelor 7 9%
Professor 6 7%
Other 13 16%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 32%
Biochemistry, Genetics and Molecular Biology 14 17%
Computer Science 11 13%
Medicine and Dentistry 10 12%
Mathematics 3 4%
Other 10 12%
Unknown 8 10%