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Comment on: 'ERGC: an efficient referential genome compression algorithm'.
- Source :
- Bioinformatics; 4/1/2016, Vol. 32 Issue 7, p1115-1117, 3p
- Publication Year :
- 2016
-
Abstract
- Motivation: Data compression is crucial in effective handling of genomic data. Among several recently published algorithms, ERGC seems to be surprisingly good, easily beating all of the competitors. Results: We evaluated ERGC and the previously proposed algorithms GDC and iDoComp, which are the ones used in the original paper for comparison, on a wide data set including 12 assemblies of human genome (instead of only four of them in the original paper). ERGC wins only when one of the genomes (referential or target) contains mixed-cased letters (which is the case for only the two Korean genomes). In all other cases ERGC is on average an order of magnitude worse than GDC and iDoComp. [ABSTRACT FROM AUTHOR]
- Subjects :
- DATA compression
GENOMICS
ALGORITHMS
HUMAN genome
BIG data
Subjects
Details
- Language :
- English
- ISSN :
- 13674803
- Volume :
- 32
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 114040791
- Full Text :
- https://doi.org/10.1093/bioinformatics/btv704