While reading tweets from #biodata14, we came across this review paper that the readers will find useful (h/t @markgerstein). We covered other research work from the authors, especially in the context of minimizer-based k-mer counting. The authors themselves also wrote a compression tool using minimizers.
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.