Abstract
Data storage is a major and growing part of IT budgets for research since many years. Especially in biology, the amount of raw data products is growing continuously, and the advent of the so-called "next-generation" sequencers has made things worse. Affordable prices have pushed scientists to massively sequence whole genomes and to screen large cohort of patients, thereby producing tons of data as a side effect. The need for maximally fitting data into the available storage volumes has encouraged and welcomed new compression algorithms and tools. We focus here on state-of-the-art compression tools and measure their compression performance on ABI SOLiD data.
Original language | English |
---|---|
Pages (from-to) | 309-318 |
Number of pages | 10 |
Journal | Algorithms |
Volume | 6 |
Issue number | 2 |
DOIs | |
Publication status | Published - Jun 2013 |
Keywords
- Data compression
- Genomics
- Next-generation sequencing
- SOLiD
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computational Mathematics
- Numerical Analysis
- Theoretical Computer Science