Abstract
The advent of High Throughput Sequencing (HTS) methods opens new opportunities for the analysis of genomes and transcriptomes. While the sequencing of a whole mammalian genome took several years at the turn of this century, today it is only a matter of weeks. The race towards the thousand-dollar genome is fueled by the – ethically challenging – idea of personalized genomic medicine. However, these methods allow new and interesting insights in many aspects such as the discovery of novel noncoding RNA classes, structural variants, or alternative splice sites to name a few. Meanwhile, several methods for HTS have been introduced to the markets. Here, an overview on the technologies and the bioinformatics analysis of HTS data is given.
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Acknowledgments
Many thanks go to Maribel Hernandez Rosales, Dulce Palafox, Ishaan Gupta, Sven Findeis, Dominic Rose, and Jörg Hackermüller for fruitful discussions and proof-reading the manuscript. This publication is supported by LIFE-Leipzig Research Center for Civilization Diseases, Universitaet Leipzig. This project was funded by means of the European Social Fund and the Free State of Saxony.
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Hoffmann, S. (2011). Computational Analysis of High Throughput Sequencing Data. In: Mayer, B. (eds) Bioinformatics for Omics Data. Methods in Molecular Biology, vol 719. Humana Press. https://doi.org/10.1007/978-1-61779-027-0_9
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DOI: https://doi.org/10.1007/978-1-61779-027-0_9
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