Answers are grounded in this paper and cite their sources.
: Post-Sanger sequencing methods produce tons of data, and there is a general agreement that the challenge to store and process them must be addressed with data compression. In this review we first answer the question "why compression" in a quantitative manner. Then we also answer the questions "what" and "how", by sketching the fundamental compression ideas, describing the main sequencing data types and formats, and comparing the specialized compression algorithms and tools. Finally, we go back to the question "why compression" and give other, perhaps surprising answers, demonstrating the pervasiveness of data compression techniques in computational biology.
No takes yet. Share an insight, caveat, or question.
Deorowicz et al. (2013) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: