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Bacterial Genomic Data Analysis in the Next-Generation Sequencing Era

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1415))

Abstract

Bacterial genome sequencing is now an affordable choice for many laboratories for applications in research, diagnostic, and clinical microbiology. Nowadays, an overabundance of tools is available for genomic data analysis. However, tools differ for algorithms, languages, hardware requirements, and user interface, and combining them as it is necessary for sequence data interpretation often requires (bio)informatics skills which can be difficult to find in many laboratories. In addition, multiple data sources, as well as exceedingly large dataset sizes, and increasingly computational complexity further challenge the accessibility, reproducibility, and transparency of the entire process. In this chapter we will cover the main bioinformatics steps required for a complete bacterial genome analysis using next-generation sequencing data, from the raw sequence data to assembled and annotated genomes. All the tools described are available in the Orione framework (http://orione.crs4.it), which uniquely combines in a transparent way the most used open source bioinformatics tools for microbiology, allowing microbiologist without any specific hardware or informatics skill to conduct data-intensive computational analyses from quality control to microbial gene annotation.

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Acknowledgments

This work was partially supported by the Sardinian Regional Authorities.

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Authors and Affiliations

  1. CRS4, Science and Technology Park Polaris, Piscina Manna, 09010, Pula, CA, Italy

    Massimiliano Orsini, Gianmauro Cuccuru, Paolo Uva & Giorgio Fotia

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  1. Massimiliano Orsini
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  2. Gianmauro Cuccuru
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  3. Paolo Uva
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  4. Giorgio Fotia
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Correspondence to Giorgio Fotia .

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Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

    Oliviero Carugo

  2. Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

    Frank Eisenhaber

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Orsini, M., Cuccuru, G., Uva, P., Fotia, G. (2016). Bacterial Genomic Data Analysis in the Next-Generation Sequencing Era. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 1415. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3572-7_21

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  • DOI: https://doi.org/10.1007/978-1-4939-3572-7_21

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