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NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data

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  • Ravi K Patel
  • Mukesh Jain

Abstract

Next generation sequencing (NGS) technologies provide a high-throughput means to generate large amount of sequence data. However, quality control (QC) of sequence data generated from these technologies is extremely important for meaningful downstream analysis. Further, highly efficient and fast processing tools are required to handle the large volume of datasets. Here, we have developed an application, NGS QC Toolkit, for quality check and filtering of high-quality data. This toolkit is a standalone and open source application freely available at http://www.nipgr.res.in/ngsqctoolkit.html. All the tools in the application have been implemented in Perl programming language. The toolkit is comprised of user-friendly tools for QC of sequencing data generated using Roche 454 and Illumina platforms, and additional tools to aid QC (sequence format converter and trimming tools) and analysis (statistics tools). A variety of options have been provided to facilitate the QC at user-defined parameters. The toolkit is expected to be very useful for the QC of NGS data to facilitate better downstream analysis.

Suggested Citation

  • Ravi K Patel & Mukesh Jain, 2012. "NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-7, February.
    • Handle: RePEc:plo:pone00:0030619
    DOI: 10.1371/journal.pone.0030619
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    6. Abrar E Al-Shaer & George R Flentke & Mark E Berres & Ana Garic & Susan M Smith, 2019. "Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-25, April.

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