Compression of whole genome alignments

Authors:
Pavol Hanus;Janis Dingel;Georg Chalkidis;Joachim Hagenauer
Affiliations:
Department of Electrical Engineering and Information Technology, Technische Universität München, München, Germany;Department of Electrical Engineering and Information Technology, Technische Universität München, München, Germany;Department of Electrical Engineering and Information Technology, Technische Universität München, München, Germany;Department of Electrical Engineering and Information Technology, Technische Universität München, München, Germany
Venue:
IEEE Transactions on Information Theory - Special issue on information theory in molecular biology and neuroscience
Year:
2010

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Abstract

Recent advances in DNA sequencing technology have caused an exponential growth of publicly available genomic sequence data. A particularly voluminous, frequently used static data set are whole genome alignments. The first lossless compression algorithm for such data sets based on well-established statistical evolutionary models and prediction techniques from lossless binary image compression is introduced. The compression rate is improved by a factor of 1.6 compared to the currently used Lempel-Ziv (LZ) compression.