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GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Minseok | - |
dc.contributor.author | Leem, Sangseob | - |
dc.contributor.author | Yoon, Joon | - |
dc.contributor.author | Park, Taesung | - |
dc.date.accessioned | 2018-05-15T02:06:13Z | - |
dc.date.available | 2018-05-15T11:07:11Z | - |
dc.date.issued | 2018-03-19 | - |
dc.identifier.citation | BMC Systems Biology, 12(Suppl 2):19 | ko_KR |
dc.identifier.issn | 1752-0509 | - |
dc.identifier.uri | https://hdl.handle.net/10371/139760 | - |
dc.description.abstract | Background
With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Results Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. Conclusion The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X. | ko_KR |
dc.description.sponsorship | This work was supported by the Bio-Synergy Research Project (2013M3A9C4078158) of the Ministry of Science, ICT and Future Planning through the National Research Foundation and by grants from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI15C2165, HI16C2037). Publication of this article was funded by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037). | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BioMed Central | ko_KR |
dc.subject | Gene-gene interaction | ko_KR |
dc.subject | Rare variant | ko_KR |
dc.subject | Multifactor dimensionality reduction | ko_KR |
dc.title | GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 권민석 | - |
dc.contributor.AlternativeAuthor | 임상섭 | - |
dc.contributor.AlternativeAuthor | 윤준 | - |
dc.contributor.AlternativeAuthor | 박태성 | - |
dc.identifier.doi | 10.1186/s12918-018-0543-4 | - |
dc.rights.holder | The Author(s). | - |
dc.date.updated | 2018-03-25T05:31:48Z | - |
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