Abstract
In the last years, advances in DNA sequencing technology have caused a giant growth in the amount of available data related with genomic sequences. One of those types of data sets is that resulting from multiple sequence alignments (MSA). In this paper, we propose a compression method for compressing these data sets, using a mixture of finite-context models and arithmetic coding. The method relies on image compression concepts, it was tested in the multiz28way data set and attained a compression rate around 0.93 bits per symbol on the sequence data, better than the ≈ 1 bit per symbol attained by a recently proposed method.
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Matos, L.M.O., Pratas, D., Pinho, A.J. (2012). Compression of Whole Genome Alignments Using a Mixture of Finite-Context Models. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31295-3_42
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DOI: https://doi.org/10.1007/978-3-642-31295-3_42
Publisher Name: Springer, Berlin, Heidelberg
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