Systematic reanalysis of genomic data improves quality of variant interpretation

S. M. Hiatt, M. D. Amaral, K. M. Bowling, C. R. Finnila, M. L. Thompson, D. E. Gray, J. M.J. Lawlor, J. N. Cochran, E. M. Bebin, K. B. Brothers, K. M. East, W. V. Kelley, N. E. Lamb, S. E. Levy, E. J. Lose, M. B. Neu, C. A. Rich, S. Simmons, R. M. Myers, G. S. BarshG. M. Cooper

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


As genomic sequencing expands, so does our knowledge of the link between genetic variation and disease. Deeper catalogs of variant frequencies improve identification of benign variants, while sequencing affected individuals reveals disease-associated variation. Accumulation of human genetic data thus makes reanalysis a means to maximize the benefits of clinical sequencing. We implemented pipelines to systematically reassess sequencing data from 494 individuals with developmental disability. Reanalysis yielded pathogenic or likely pathogenic (P/LP) variants that were not initially reported in 23 individuals, 6 described here, comprising a 16% increase in P/LP yield. We also downgraded 3 LP and 6 variants of uncertain significance (VUS) due to updated population frequency data. The likelihood of identifying a new P/LP variant increased over time, as ~22% of individuals who did not receive a P/LP variant at their original analysis subsequently did after 3 years. We show here that reanalysis and data sharing increase the diagnostic yield and accuracy of clinical sequencing.

Original languageEnglish
Pages (from-to)174-178
Number of pages5
JournalClinical Genetics
Issue number1
StatePublished - Jul 2018


  • CSER
  • VUS
  • clinical sequencing
  • data sharing
  • developmental delay
  • intellectual disability
  • reanalysis


Dive into the research topics of 'Systematic reanalysis of genomic data improves quality of variant interpretation'. Together they form a unique fingerprint.

Cite this