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Integrative information theoretic network analysis for genome-wide association study of aspirin exacerbated respiratory disease in Korean population

Overview of attention for article published in BMC Medical Genomics, May 2017
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Title
Integrative information theoretic network analysis for genome-wide association study of aspirin exacerbated respiratory disease in Korean population
Published in
BMC Medical Genomics, May 2017
DOI 10.1186/s12920-017-0266-1
Pubmed ID
Authors

Wang, Sehee, Jeong, Hyun-hwan, Kim, Dokyoon, Wee, Kyubum, Park, Hae-Sim, Kim, Seung-Hyun, Sohn, Kyung-Ah

Abstract

Aspirin Exacerbated Respiratory Disease (AERD) is a chronic medical condition that encompasses asthma, nasal polyposis, and hypersensitivity to aspirin and other non-steroidal anti-inflammatory drugs. Several previous studies have shown that part of the genetic effects of the disease may be induced by the interaction of multiple genetic variants. However, heavy computational cost as well as the complexity of the underlying biological mechanism has prevented a thorough investigation of epistatic interactions and thus most previous studies have typically considered only a small number of genetic variants at a time. In this study, we propose a gene network based analysis framework to identify genetic risk factors from a genome-wide association study dataset. We first derive multiple single nucleotide polymorphisms (SNP)-based epistasis networks that consider marginal and epistatic effects by using different information theoretic measures. Each SNP epistasis network is converted into a gene-gene interaction network, and the resulting gene networks are combined as one for downstream analysis. The integrated network is validated on existing knowledgebase of DisGeNET for known gene-disease associations and GeneMANIA for biological function prediction. We demonstrated our proposed method on a Korean GWAS dataset, which has genotype information of 440,094 SNPs for 188 cases and 247 controls. The topological properties of the generated networks are examined for scale-freeness, and we further performed various statistical analyses in the Allergy and Asthma Portal (AAP) using the selected genes from our integrated network. Our result reveals that there are several gene modules in the network that are of biological significance and have evidence for controlling susceptibility and being related to the treatment of AERD.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 24%
Student > Ph. D. Student 3 14%
Student > Doctoral Student 2 10%
Student > Master 2 10%
Librarian 1 5%
Other 3 14%
Unknown 5 24%
Readers by discipline Count As %
Medicine and Dentistry 5 24%
Biochemistry, Genetics and Molecular Biology 2 10%
Pharmacology, Toxicology and Pharmaceutical Science 2 10%
Immunology and Microbiology 1 5%
Physics and Astronomy 1 5%
Other 3 14%
Unknown 7 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 July 2018.
All research outputs
#10,134,351
of 13,272,830 outputs
Outputs from BMC Medical Genomics
#478
of 664 outputs
Outputs of similar age
#177,784
of 267,631 outputs
Outputs of similar age from BMC Medical Genomics
#12
of 15 outputs
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