Sebastian Deorowicz, S. Grabowski
2013.1.1Algorithms for Molecular Biology
tlooto Summary
This review answers the question “why compression” in a quantitative manner, and gives other, perhaps surprising answers, demonstrating the pervasiveness of datacompression techniques in computational biology.
Abstract
Post-Sanger sequencing methods produce tons of data, and there is a generalagreement that the challenge to store and process them must be addressedwith data compression. In this review we first answer the question“why compression” in a quantitative manner. Then we also answerthe questions “what” and “how”, by sketching thefundamental compression ideas, describing the main sequencing data types andformats, and comparing the specialized compression algorithms and tools.Finally, we go back to the question “why compression” and giveother, perhaps surprising answers, demonstrating the pervasiveness of datacompression techniques in computational biology.
Citation format
DEOROWICZ, Sebastian; GRABOWSKI, S. Data compression for sequencing data. Algorithms for Molecular Biology, 2013, 8: 25–25.