HapTree: A novel bayesian framework for single individual polyplotyping using NGS data

Emily Berger, Deniz Yorukoglu, Jian Peng, Bonnie Berger

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

Abstract

Using standard genotype calling tools, it is possible to accurately identify the number of "wild type" and "mutant" alleles (A, C, G, or T) for each singlenucleotide polymorphism (SNP) site. In the case of two heterozygous SNP sites however, genotype calling tools cannot determine whether "mutant" alleles from different SNP loci are on the same or different chromosomes. While in many cases the former would be healthy, the latter can cause loss of function; it is therefore important to identify the phase - the copies of a chromosome on which the mutant alleles occur - in addition to the genotype. This need necessitates efficient algorithms to obtain an accurate and comprehensive haplotype reconstruction (the phase of heterozygous SNPs in the genome) directly from the next-generation sequencing (NGS) read data. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes of higher ploidy; however, computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as studies into the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 18th Annual International Conference, RECOMB 2014, Proceedings
PublisherSpringer
Pages18-19
Number of pages2
ISBN (Print)9783319052687
DOIs
StatePublished - 2014
Externally publishedYes
Event18th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2014 - Pittsburgh, PA, United States
Duration: Apr 2 2014Apr 5 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8394 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2014
Country/TerritoryUnited States
CityPittsburgh, PA
Period4/2/144/5/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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