In genomics, DNA sequencing is the process of converting information stored in nucleic acid into digital data that can be stored inside computers, and the amount of storage required can be reduced with loseless compression. As the rise of modern high throughput sequencing methods allow for more genetic material to be processed, the increased amount of data generated demands extra storage space, and more efficient methods of storage were desired. The application of computer science and mathematics into the field spawned new compression algorithms optimized specifically for the storage of genetic material. These technologies are enabling ambitious genome sequencing endeavours, such as the 1000 Genomes Project and 1001 (Arabidopsis thaliana) Genomes Project. The storage and transfer of the tremendous amount of genomic data have become a mainstream problem, motivating the development of high-performance compression tools designed specifically for genomic data. A recent surge of interest in the development of novel algorithms and tools for storing and managing genomic re-sequencing data emphasizes the growing demand for efficient methods for genomic data compression.
Nalbantog̃Lu, O. U.; Russell, D. J.; Sayood, K. (2010).
"Data Compression Concepts and Algorithms and their Applications to Bioinformatics".
Entropy.
12 (1): 34.
doi:
10.3390/e12010034.
PMC 2821113.
PMID 20157640.
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↑ Lan, Divon; Llamas, Bastien (14 September 2022). "Genozip 14 - advances in compression of BAM and CRAM files". bioRxiv 10.1101/2022.09.12.507582.
↑ "ISO/IEC 23092-2:2019 Information technology — Genomic information representation — Part 2: Coding of genomic information". iso.org.
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