Genetic variants contribute significantly to the etiology of autism, and unlike single-nucleotide variants (SNVs), copy number variants (CNVs) are more difficult to detect from genetic sequencing datasets. The goal of this proposal is to significantly increase the yield of high-impact autism mutations by focusing on the discovery of both CNVs and SNVs in autism families from SPARK. Using established and novel computational pipelines, Evan Eichler and colleagues propose to work with the SPARK Consortium to generate a high-confidence set of potential pathogenic variants and then integrate these data into larger genetic variant databases to pinpoint pathogenic variants and novel genes associated with autism.