Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR
| Autor: | Alexey A. Shadrin, Srdjan Djurovic, Ole A. Andreassen, Anders M. Dale, Dominic Holland, Olav B. Smeland, Oleksandr Frei, Shahram Bahrami, Francesco Bettella, Tea Kristiane Espeland Uggen, Osman A. B. S. M. Gani, Kevin S. O’Connell |
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| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
AcademicSubjects/SCI01060 Genome-wide association study Computational biology Biology Biochemistry Genome 03 medical and health sciences Annotation 0302 clinical medicine medicine Humans Bipolar disorder Molecular Biology Gene 030304 developmental biology Genetic association 0303 health sciences Likelihood Functions Genetics and Population Analysis medicine.disease Phenotype Original Papers Computer Science Applications Computational Mathematics Computational Theory and Mathematics Diabetes Mellitus Type 2 Schizophrenia 030217 neurology & neurosurgery Software Genome-Wide Association Study |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4803 |
| Popis: | Motivation Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Results Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, Availability and implementation The software is available at: https://github.com/precimed/mixer. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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