Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset
Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underly...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Korea Genome Organization
2013-09-01
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| Series: | Genomics & Informatics |
| Subjects: | |
| Online Access: | http://genominfo.org/upload/pdf/gni-11-135.pdf |
| _version_ | 1818260276793835520 |
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| author | Jihye Kim Ji-sun Kwon Sangsoo Kim |
| author_facet | Jihye Kim Ji-sun Kwon Sangsoo Kim |
| author_sort | Jihye Kim |
| collection | DOAJ |
| description | Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP) genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO) terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr < 0.05). Pairwise comparison of the traits in terms of the semantic similarity in their GO sets revealed surprising cases where phenotypically uncorrelated traits showed high similarity in terms of biological pathways. For example, the pH level was related to 7 other traits that showed low phenotypic correlations with it. A literature survey implies that these traits may be regulated partly by common pathways that involve neuronal or nerve systems. |
| first_indexed | 2024-12-12T18:28:46Z |
| format | Article |
| id | doaj.art-199d89e9ae1b4a95952fec1534c694e6 |
| institution | Directory Open Access Journal |
| issn | 1598-866X 2234-0742 |
| language | English |
| last_indexed | 2024-12-12T18:28:46Z |
| publishDate | 2013-09-01 |
| publisher | Korea Genome Organization |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj.art-199d89e9ae1b4a95952fec1534c694e62022-12-22T00:15:58ZengKorea Genome OrganizationGenomics & Informatics1598-866X2234-07422013-09-0111313514110.5808/GI.2013.11.3.13548Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology DatasetJihye Kim0Ji-sun Kwon1Sangsoo Kim2Department of Bioinformatics and Life Science, Soongsil University, Seoul 156-743, Korea.Department of Bioinformatics and Life Science, Soongsil University, Seoul 156-743, Korea.Department of Bioinformatics and Life Science, Soongsil University, Seoul 156-743, Korea.Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP) genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO) terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr < 0.05). Pairwise comparison of the traits in terms of the semantic similarity in their GO sets revealed surprising cases where phenotypically uncorrelated traits showed high similarity in terms of biological pathways. For example, the pH level was related to 7 other traits that showed low phenotypic correlations with it. A literature survey implies that these traits may be regulated partly by common pathways that involve neuronal or nerve systems.http://genominfo.org/upload/pdf/gni-11-135.pdfGene Ontologygene set analysisgenome-wide association studyquantitative traitssemantic similarity |
| spellingShingle | Jihye Kim Ji-sun Kwon Sangsoo Kim Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset Genomics & Informatics Gene Ontology gene set analysis genome-wide association study quantitative traits semantic similarity |
| title | Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset |
| title_full | Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset |
| title_fullStr | Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset |
| title_full_unstemmed | Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset |
| title_short | Gene Set Analyses of Genome-Wide Association Studies on 49 Quantitative Traits Measured in a Single Genetic Epidemiology Dataset |
| title_sort | gene set analyses of genome wide association studies on 49 quantitative traits measured in a single genetic epidemiology dataset |
| topic | Gene Ontology gene set analysis genome-wide association study quantitative traits semantic similarity |
| url | http://genominfo.org/upload/pdf/gni-11-135.pdf |
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