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

PLoS ONE · 2012 · Vol. 7(2) · pp. e30619–e30619
Ravi K. PatelMukesh 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.

Genomics and Phylogenetic StudiesAlgorithms and Data CompressionMicrobial Community Ecology and PhysiologyPerlComputer sciencePython (programming language)Downstream (manufacturing)Data miningWorld Wide WebOperating system

MeSH terms

Quality ControlStatistics as TopicSequence AnalysisDNA PrimersData CompressionPolymerizationHigh-Throughput Nucleotide Sequencing
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References
RNA-Seq: a revolutionary tool for transcriptomics
Nature Reviews Genetics · 2008 · 13,223 citations
Quality control and preprocessing of metagenomic datasets
Bioinformatics · 2011 · 5,319 citations
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