A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia.
dc.contributor.author | Jia, Peilin | |
dc.contributor.author | Wang, Lily | |
dc.contributor.author | Fanous, Ayman H | |
dc.contributor.author | Chen, Xiangning | |
dc.contributor.author | Kendler, Kenneth S | |
dc.contributor.author | Zhao, Zhongming | |
dc.date.accessioned | 2012-08-15T14:06:58Z | |
dc.date.available | 2012-08-15T14:06:58Z | |
dc.date.issued | 2012-02 | |
dc.identifier.citation | A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia. 2012, 49 (2):96-103 J. Med. Genet. | en_GB |
dc.identifier.issn | 1468-6244 | |
dc.identifier.pmid | 22187495 | |
dc.identifier.doi | 10.1136/jmedgenet-2011-100397 | |
dc.identifier.uri | http://hdl.handle.net/10147/238786 | |
dc.description.abstract | After the recent successes of genome-wide association studies (GWAS), one key challenge is to identify genetic variants that might have a significant joint effect on complex diseases but have failed to be identified individually due to weak to moderate marginal effect. One popular and effective approach is gene set based analysis, which investigates the joint effect of multiple functionally related genes (eg, pathways). However, a typical gene set analysis method is biased towards long genes, a problem that is especially severe in psychiatric diseases. | |
dc.language.iso | en | en |
dc.rights | Archived with thanks to Journal of medical genetics | en_GB |
dc.subject.mesh | Cell Adhesion Molecules | |
dc.subject.mesh | Computational Biology | |
dc.subject.mesh | Databases, Genetic | |
dc.subject.mesh | Genetic Predisposition to Disease | |
dc.subject.mesh | Genome-Wide Association Study | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Immune System | |
dc.subject.mesh | Major Histocompatibility Complex | |
dc.subject.mesh | Polymorphism, Single Nucleotide | |
dc.subject.mesh | Schizophrenia | |
dc.subject.mesh | Signal Transduction | |
dc.title | A bias-reducing pathway enrichment analysis of genome-wide association data confirmed association of the MHC region with schizophrenia. | en_GB |
dc.type | Article | en |
dc.contributor.department | Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA. | en_GB |
dc.identifier.journal | Journal of medical genetics | en_GB |
dc.description.province | Leinster | en |
html.description.abstract | After the recent successes of genome-wide association studies (GWAS), one key challenge is to identify genetic variants that might have a significant joint effect on complex diseases but have failed to be identified individually due to weak to moderate marginal effect. One popular and effective approach is gene set based analysis, which investigates the joint effect of multiple functionally related genes (eg, pathways). However, a typical gene set analysis method is biased towards long genes, a problem that is especially severe in psychiatric diseases. |