An SVM-based approach for genotyping deletions and insertions with population sequence reads

Chong Chu, Jin Zhang, Yufeng Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Because of the low quality and large size of population sequence data, calling population structural variations (SVs) genotypes is still a challenging problem. In this paper, we propose an SVM-based approach for genotyping deletion and insertion polymorphisms with population sequence reads. The key idea of our approach is combining multiple sources of information contained in sequence data in calling genotypes. Results on both simulated and real data suggest that our approach works well.

Original languageEnglish
Title of host publication2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013
DOIs
StatePublished - Dec 9 2013
Event2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013 - New Orleans, LA, United States
Duration: Jun 12 2013Jun 14 2013

Publication series

Name2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013

Conference

Conference2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013
Country/TerritoryUnited States
CityNew Orleans, LA
Period06/12/1306/14/13

Keywords

  • genotype calling
  • high-throughput sequencing
  • structural variation

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