Comment on: 'ERGC: an efficient referential genome compression algorithm'.
Bioinformatics
; 32(7): 1115-7, 2016 04 01.
Article
em En
| MEDLINE
| ID: mdl-26615213
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. CONTACT sebastian.deorowicz@polsl.pl, iochoa@stanford.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência de DNA
/
Compressão de Dados
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article