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A computational genomics pipeline for prokaryotic sequencing projects

2010; Oxford University Press; Volume: 26; Issue: 15 Linguagem: Inglês

10.1093/bioinformatics/btq284

1367-4811

Andrey Kislyuk, Lee S. Katz, Sonia Agrawal, Matthew S Hagen, Andrew B. Conley, Pushkala Jayaraman, Viswateja Nelakuditi, Jay C. Humphrey, Scott A. Sammons, Dhwani Govil, Raydel Mair, Kathleen M. Tatti, M. Lucia Tondella, Brian H. Harcourt, Leonard W. Mayer, I. King Jordan,

Infective Endocarditis Diagnosis and Management

Abstract Motivation: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. Results: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. Availability and implementation: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems. Contact: king.jordan@biology.gatech.edu Supplementary information: Supplementary data are available at Bioinformatics online.