Genome-wide transcriptome profiling reveals the functional impact of rare de novo and recurrent CNVs in autism: implications for analysis of rare variants in sequence data

Daniel Geschwind
University of California, Los Angeles (UCLA)

A key issue in genomics and genetics is to sift through the many forms of rare variation identified in disease populations to identify those that are most likely to be pathogenic. We have used lymphoblast gene expression to identify genes with large changes in individual patients, deemed outliers, to identify genes harboring potential mutations. We show how this approach can help prioritize and characterize CNV, as well as SNV identified in genetic studies, using autism and intellectual disability as examples.

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