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Detecting false-positive signals in exome sequencing†

  1. Karin V. Fuentes Fajardo1,
  2. David Adams1,2,
  3. NISC Comparative Sequencing Program3,
  4. Christopher E. Mason4,5,
  5. Murat Sincan2,
  6. Cynthia Tifft1,2,
  7. Camilo Toro1,
  8. Cornelius F Boerkoel1,
  9. William Gahl1,2,6,
  10. Thomas Markello6,*

Article first published online: 5 MAR 2012

DOI: 10.1002/humu.22033

Issue

Human Mutation

Human Mutation

Special Issue: Focus on the NIH Undiagnosed Diseases Program

Volume 33, Issue 4, pages 609–613, April 2012

Additional Information

How to Cite

Fuentes Fajardo, K. V., Adams, D., NISC Comparative Sequencing Program, Mason, C. E., Sincan, M., Tifft, C., Toro, C., Boerkoel, C. F., Gahl, W. and Markello, T. (2012), Detecting false-positive signals in exome sequencing. Hum. Mutat., 33: 609–613. doi: 10.1002/humu.22033

Author Information

  1. 1

    NIH Undiagnosed Diseases Program, NIH Office of Rare Diseases Research and NHGRI, Bethesda, Maryland

  2. 2

    Medical Genetics Branch, NHGRI, NIH, Bethesda, Maryland

  3. 3

    NIH Intramural Sequencing Center, NIH, Bethesda, Maryland

  4. 4

    Department of Physiology and Biophysics, Weill Medical College, Cornell University, New York, New York

  5. 5

    HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, New York

  6. 6

    Office of the Clinical Director, NHGRI, NIH, Bethesda, Maryland

*Thomas C Markello, Medical Genetics Branch, NIH/NHGRI, 10 Center Drive, Building 10/10C103, Bethesda, MD 20892

  1. †

    For the Focus on the NIH Undiagnosed Diseases Program

Publication History

  1. Issue published online: 12 MAR 2012
  2. Article first published online: 5 MAR 2012
  3. Accepted manuscript online: 31 JAN 2012 12:00AM EST
  4. Manuscript Accepted: 2 DEC 2011
  5. Manuscript Received: 11 AUG 2011

Funded by

  • NHGRI intramural funding; UDP program through the office of the Director NIH

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Keywords:

  • Exome sequencing;
  • inherited disease;
  • false positives;
  • next generation sequencing;
  • genomics;
  • Illumina;
  • sequencing errors;
  • alignment errors;
  • WES;
  • SureSelect Human All Exon

Abstract

Disease gene discovery has been transformed by affordable sequencing of exomes and genomes. Identification of disease-causing mutations requires sifting through a large number of sequence variants. A subset of the variants are unlikely to be good candidates for disease causation based on one or more of the following criteria: (1) being located in genomic regions known to be highly polymorphic, (2) having characteristics suggesting assembly misalignment, and/or (3) being labeled as variants based on misleading reference genome information. We analyzed exome sequence data from 118 individuals in 29 families seen in the NIH Undiagnosed Diseases Program (UDP) to create lists of variants and genes with these characteristics. Specifically, we identified several groups of genes that are candidates for provisional exclusion during exome analysis: 23,389 positions with excess heterozygosity suggestive of alignment errors and 1,009 positions in which the hg18 human genome reference sequence appeared to contain a minor allele. Exclusion of such variants, which we provide in supplemental lists, will likely enhance identification of disease-causing mutations using exome sequence data. Hum Mutat 33:609–613, 2012. © 2012 Wiley Periodicals, Inc.

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