New mutations, old statistical challenges
Jeffrey C Barrett,
Joseph D. Buxbaum,
David J. Cutler,
Mark J. Daly,
Matthew E Hurles,
Jack A. Kosmicki,
Eric S Lander,
Daniel G. MacArthur,
Benjamin M. Neale,
Peter M Visscher,
Naomi R Wray
Posted 12 Mar 2017
bioRxiv DOI: 10.1101/115964
Posted 12 Mar 2017
Based on targeted sequencing of 208 genes in 11,730 neurodevelopmental disorder cases, Stessman et al. report the identification of 91 genes associated (at a False Discovery Rate [FDR] of 0.1) with autism spectrum disorders (ASD), intellectual disability (ID), and developmental delay (DD)-including what they characterize as 38 novel genes, not previously reported as connected with these diseases. If true, this would represent a substantial step forward. Unfortunately, each of the two discovery analyses (1. De novo mutation analysis and, 2. a comparison of private mutations with public control data) contain critical statistical flaws. When one accounts for these problems, fewer than half of the genes-and very few, if any, of the novel findings-survive. These errors have implications for how future analyses should be conducted, for understanding the genetic basis of these disorders, and for genomic medicine. We discuss the two main analyses in turn and provide more detailed treatment of the issues in a supplementary technical note.
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