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

Author

Chong Chu ; Jin Zhang ; Yufeng Wu

Author_Institution

Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT, USA

fYear

2013

fDate

12-14 June 2013

Firstpage

1

Lastpage

1

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.

Keywords

biology computing; genomics; molecular biophysics; molecular configurations; polymorphism; support vector machines; SVM-based approach; calling genotypes; data sequence; genotyping deletions; genotyping insertions; multiple information sources; polymorphisms; population sequence data; population sequence reads; population structural variations; Bioinformatics; Educational institutions; Electronic mail; Genomics; Sociology; Statistics; Support vector machines; genotype calling; highthroughputsequencing.; structural variation;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

New Orleans, LA

Type

conf

DOI

10.1109/ICCABS.2013.6629219

Filename

6629219