CoLoRMap: Correcting Long Reads by Mapping short reads
Author(s) -
Ehsan Haghshenas,
Faraz Hach,
S. Cenk Şahinalp,
Cédric Chauve
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw463
Subject(s) - computer science , leverage (statistics) , sequence assembly , source code , reference genome , dna sequencing , algorithm , data mining , computational biology , biology , artificial intelligence , genetics , gene , programming language , gene expression , transcriptome
Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characterized by a high error rate, and assembling from long reads require a high depth of coverage. This motivates the development of hybrid approaches that leverage the high quality of short reads to correct errors in long reads.
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