Identification of Rare Causal Variants in Sequence-Based Studies: Methods and Applications to , a Gene Involved in Cohen Syndrome and Autism

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Sequencing technologies allow identification of genetic variants down to single base resolution for a whole human genome. The vast majority of these variants (over 90%) are rare, with population frequencies less than 1%. Furthermore, in a specific study, many of the variants identified are not associated with the disease of interest, and identification of the small proportion of truly causal variants is a difficult task. Clearly, for causal variants that are rare enough to only appear a few times in a study, observed frequencies in cases and controls are not enough to distinguish them from the vast majority of random variation, and rich functional annotations can help identify the causal variants. Here we propose to develop a set of statistical methods that leverage diverse functional genomics annotations with sequencing data to identify a small set of potentially causal variants and estimate their effects. Pinpointing a subset of potentially causal variants is crucial for understanding precise biological mechanisms, and for further experimental functional studies.

Vyšlo v časopise: Identification of Rare Causal Variants in Sequence-Based Studies: Methods and Applications to , a Gene Involved in Cohen Syndrome and Autism. PLoS Genet 10(12): e32767. doi:10.1371/journal.pgen.1004729
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004729

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