Software review

SNIT: SNP identification for strain typing

Ravi Vijaya Satya, Nela Zavaljevski and Jaques Reifman^*

• * Corresponding author: Jaques Reifman jaques.reifman@us.army.mil

Author Affiliations

Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD 21702, USA

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Source Code for Biology and Medicine 2011, 6:14 doi:10.1186/1751-0473-6-14

Published: 8 September 2011

Abstract

With ever-increasing numbers of microbial genomes being sequenced, efficient tools are needed to perform strain-level identification of any newly sequenced genome. Here, we present the SNP identification for strain typing (SNIT) pipeline, a fast and accurate software system that compares a newly sequenced bacterial genome with other genomes of the same species to identify single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels). Based on this information, the pipeline analyzes the polymorphic loci present in all input genomes to identify the genome that has the fewest differences with the newly sequenced genome. Similarly, for each of the other genomes, SNIT identifies the input genome with the fewest differences. Results from five bacterial species show that the SNIT pipeline identifies the correct closest neighbor with 75% to 100% accuracy. The SNIT pipeline is available for download at http://www.bhsai.org/snit.html webcite