PT29 – Fast genotyping of known SNPs through approximate k-mer matching

Proceeding talk – Theme: Genome.

Abstract

We introduce LAVA (Lightweight Assignment of Variant Alleles), an NGS-based genotyping algorithm for a given set of SNP loci, which takes advantage of the fact that approximate matching of mid-size k-mers (with k = 32) can typically uniquely identify loci in the human genome without full read alignment. LAVA accurately calls the vast majority of SNPs in dbSNP and Affymetrix’s Genome-Wide Human SNP Array 6.0 up to about an order of magnitude faster than standard NGS genotyping pipelines. For Affymetrix SNPs, LAVA has significantly higher SNP calling accuracy than existing pipelines while using as low as ∼5GB of RAM. As such, LAVA represents a scalable computational method for population-level genotyping studies as well as a flexible NGS-based replacement for SNP arrays.

Link to PDF file

Authors

Konstantinos D. Tsirigos, Department of Biochemistry and Biophysics / Stockholm University, Sweden
Arne Elofsson, Department of Biochemistry and Biophysics / Stockholm University, Sweden
Pantelis G. Bagos, Department of Computer Science and Biomedical Informatics / University of Thessaly, Greece