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ABSTRACT: Purpose
Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene-disease associations.Methods
We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients.Results
We obtained a genetic diagnosis for 29 (24%) of our patients. We
SUBMITTER: Zhu X
PROVIDER: S-EPMC4791490 | biostudies-literature | 2015 Oct
REPOSITORIES: biostudies-literature