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What and Who
Title:Haplotype-Aware Genotyping from Long Sequencing Reads
Speaker:Jana Ebler
coming from:Fachrichtung Informatik - Saarbr├╝cken
Speakers Bio:MSc in Bioinformatics estimated January 2018
Event Type:PhD Application Talk
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Tuesday, 10 October 2017
Duration:60 Minutes
Building:E1 4
Genetic variations of an individuals' DNA, like Single Nucleotide Variants (SNVs) or Indels (Insertions and Deletions), can play important roles in many diseases. Therefore, genotyping variants, that is, determining their zygosity status, is an important step in analyzing such diseases. The general approach to genotyping from sequencing data is to analyze reads covering the corresponding regions in the genome. Current genotyping approaches rely on short sequencing reads from second generation sequencing devices for this task.

In my talk, I present novel algorithms able to use long sequencing reads from third generation sequencing platforms to genotype SNVs and indels. These platforms come with the drawback of high sequencing error rates. On the positive side, they provide information from neighboring variants, but this has, so far, not been exploited for genotyping. We provide a way to achieve this by considering bipartitions of all given sequencing reads, corresponding to the two haplotypes. We formalize this computational problem in terms of a Hidden Markov Model and compute posterior genotype probabilities using the Forward-Backward algorithm. Genotype predictions can then be made by picking the likeliest genotype at each site. Our experiments confirm that this approach allows to leverage the power of long sequencing reads for genotyping, which current genotypers are not able to do.

Name(s):IMPRS Office Team
Phone:0681 93251800
EMail:--email address not disclosed on the web
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Created by:Aaron Alsancak/MPI-INF, 10/09/2017 02:03 PMLast modified by:Uwe Brahm/MPII/DE, 10/10/2017 07:01 AM
  • Aaron Alsancak, 10/09/2017 02:26 PM -- Created document.