Identification of deletion polymorphisms from haplotypes

Erik Corona, Benjamin Raphael, Eleazar Eskin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Numerous efforts are underway to catalog genetic variation in human populations. While the majority of studies of genetic variation have focused on single base pair differences between individuals, i.e. single nucleotide polymorphisms (SNPs), several recent studies have demonstrated that larger scale structural variation including copy number polymorphisms and inversion polymorphisms are also common. However, direct techniques for detection and validation of structural variants are generally much more expensive than detection and validation of SNPs. For some types of structural variation, in particular deletions, the polymorphism produces a distinct signature in the SNP data. In this paper, we describe a new probabilistic method for detecting deletion polymorphisms from SNP data. The key idea in our method is that we estimate the frequency of the haplotypes in a region of the genome both with and without the possibility of a deletion in the region and apply a generalized likelihood ratio test to assess the significance of a deletion. Application of our method to the HapMap Phase 1 data revealed 319 candidate deletions, 142 of these overlap with variants identified in earlier studies, while 177 are novel. Using Phase II HapMap data we predict 6730 deletions.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
Pages354-365
Number of pages12
StatePublished - Aug 3 2007
Externally publishedYes
Event11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007 - Oakland, CA, United States
Duration: Apr 21 2007Apr 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4453 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
CountryUnited States
CityOakland, CA
Period4/21/074/25/07

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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