Sensitive quantification of mosaicism using high density SNP arrays and the cumulative distribution function

Thomas C. Markello, Hannah Carlson-Donohoe, Murat Sincan, David Adams, David M. Bodine, Jason E. Farrar, Adrianna Vlachos, Jeffrey M. Lipton, Arleen D. Auerbach, Elaine A. Ostrander, Settara C. Chandrasekharappa, Cornelius F. Boerkoel, William A. Gahl

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Medicine is rapidly applying exome and genome sequencing to the diagnosis and management of human disease. Somatic mosaicism, however, is not readily detectable by these means, and yet it accounts for a significant portion of undiagnosed disease. We present a rapid and sensitive method, the Continuous Distribution Function as applied to single nucleotide polymorphism (SNP) array data, to quantify somatic mosaicism throughout the genome. We also demonstrate application of the method to novel diseases and mechanisms.

Original languageEnglish (US)
Pages (from-to)665-671
Number of pages7
JournalMolecular Genetics and Metabolism
Volume105
Issue number4
DOIs
StatePublished - Apr 2012

Keywords

  • Array comparative genomic hybridization
  • CGH
  • Continuous Distribution Function
  • DANFIP
  • Distribution Analysis by Fitting Integrated Probabilities
  • Mosaicism

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology
  • Genetics
  • Endocrinology

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    Markello, T. C., Carlson-Donohoe, H., Sincan, M., Adams, D., Bodine, D. M., Farrar, J. E., Vlachos, A., Lipton, J. M., Auerbach, A. D., Ostrander, E. A., Chandrasekharappa, S. C., Boerkoel, C. F., & Gahl, W. A. (2012). Sensitive quantification of mosaicism using high density SNP arrays and the cumulative distribution function. Molecular Genetics and Metabolism, 105(4), 665-671. https://doi.org/10.1016/j.ymgme.2011.12.015