NGSEP3: accurate variant calling across species and sequencing protocols

Author:

Tello Daniel1,Gil Juanita1,Loaiza Cristian D2,Riascos John J2,Cardozo Nicolás1,Duitama Jorge13

Affiliation:

1. Systems and Computing Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia

2. Biotechnology lab, Centro de Investigación de la caña de azúcar de Colombia, CENICAÑA, Cali 760046, Colombia

3. Agrobiodiversity Research Area, International Center for Tropical Agriculture, Cali 763537, Colombia

Abstract

Abstract Motivation Accurate detection, genotyping and downstream analysis of genomic variants from high-throughput sequencing data are fundamental features in modern production pipelines for genetic-based diagnosis in medicine or genomic selection in plant and animal breeding. Our research group maintains the Next-Generation Sequencing Experience Platform (NGSEP) as a precise, efficient and easy-to-use software solution for these features. Results Understanding that incorrect alignments around short tandem repeats are an important source of genotyping errors, we implemented in NGSEP new algorithms for realignment and haplotype clustering of reads spanning indels and short tandem repeats. We performed extensive benchmark experiments comparing NGSEP to state-of-the-art software using real data from three sequencing protocols and four species with different distributions of repetitive elements. NGSEP consistently shows comparative accuracy and better efficiency compared to the existing solutions. We expect that this work will contribute to the continuous improvement of quality in variant calling needed for modern applications in medicine and agriculture. Availability and implementation NGSEP is available as open source software at http://ngsep.sf.net. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Global Rice Science Partnership

CGIAR Research Program

Universidad de los Andes

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference42 articles.

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