SNIT: SNP Identification for Strain Typing

Abstract

With ever-increasing numbers of microbial genomes being sequenced, efficient tools are needed to perform strainlevel 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

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2011
Accession Number
ADA571154

Entities

People

  • Jaques Reifman
  • Nela Zavaljevski
  • Ravi V. Satya

Organizations

  • United States Army Medical Research and Development Command

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accuracy
  • Application Software
  • Assembly
  • Biomedical Research
  • Computer Programming
  • Computer Programs
  • Data Sets
  • Department Of Defense
  • Errors
  • Graphical User Interface
  • High Performance Computing
  • Identification
  • Operating Systems
  • Pipelines
  • Pipes
  • Programming Languages
  • User Interface

Fields of Study

  • Biology

Readers

  • Gender and Food Studies
  • Molecular Genetics

Technology Areas

  • Biotechnology