Title |
The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study
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Published in |
BioData Mining, September 2014
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DOI | 10.1186/1756-0381-7-19 |
Pubmed ID | |
Authors |
Magnus Lekman, Ola Hössjer, Peter Andrews, Henrik Källberg, Daniel Uvehag, Dennis Charney, Husseini Manji, John A Rush, Francis J McMahon, Jason H Moore, Ingrid Kockum |
Abstract |
Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. |
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Student > Postgraduate | 3 | 6% |
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Computer Science | 4 | 8% |
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