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WISARD: workbench for integrated superfast association studies for related datasets
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sungyoung | - |
dc.contributor.author | Choi, Sungkyoung | - |
dc.contributor.author | Qiao, Dandi | - |
dc.contributor.author | Cho, Michael | - |
dc.contributor.author | Silverman, Edwin K | - |
dc.contributor.author | Park, Taesung | - |
dc.contributor.author | Won, Sungho | - |
dc.date.accessioned | 2018-05-29T02:24:14Z | - |
dc.date.available | 2018-05-29T11:25:37Z | - |
dc.date.issued | 2018-04-20 | - |
dc.identifier.citation | BMC Medical Genomics, 11(Suppl 2):39 | ko_KR |
dc.identifier.issn | 1755-8794 | - |
dc.identifier.uri | https://hdl.handle.net/10371/141243 | - |
dc.description.abstract | Background
A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies—from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. Results We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. Conclusions Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value. | ko_KR |
dc.description.sponsorship | This research was supported by grants of 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 (HI16C2037). This work was supported by the Bio-Synergy Research Project (2013M3A9C4078158, NRF-2017M3A9C4065964) of the Ministry of Science, ICT and Future Planning through the National Research Foundation. The Boston EOCOPD Study was supported by NIH R01 HL113264. The publication of this article was sponsored by the Bio-Synergy Research Project (2013M3A9C4078158). | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BioMed Central | ko_KR |
dc.subject | Family-based design | ko_KR |
dc.subject | Genome-wide association analyses | ko_KR |
dc.subject | Next generation sequencing | ko_KR |
dc.subject | Multi-threaded analyses | ko_KR |
dc.subject | Related samples | ko_KR |
dc.title | WISARD: workbench for integrated superfast association studies for related datasets | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 이성영 | - |
dc.contributor.AlternativeAuthor | 최성경 | - |
dc.contributor.AlternativeAuthor | 박태성 | - |
dc.contributor.AlternativeAuthor | 원성호 | - |
dc.identifier.doi | 10.1186/s12920-018-0345-y | - |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s). | - |
dc.date.updated | 2018-04-22T03:31:52Z | - |
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