Title
A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads.
Abstract
Novel high-throughput sequencing technologies pose new algorithmic challenges in handling massive amounts of short-read, high-coverage data. A robust and versatile consensus tool is of particular interest for such data since a sound multi-read alignment is a prerequisite for variation analyses, accurate genome assemblies and insert sequencing.A multi-read alignment algorithm for de novo or reference-guided genome assembly is presented. The program identifies segments shared by multiple reads and then aligns these segments using a consistency-enhanced alignment graph. On real de novo sequencing data obtained from the newly established NCBI Short Read Archive, the program performs similarly in quality to other comparable programs. On more challenging simulated datasets for insert sequencing and variation analyses, our program outperforms the other tools.The consensus program can be downloaded from http://www.seqan.de/projects/consensus.html. It can be used stand-alone or in conjunction with the Celera Assembler. Both application scenarios as well as the usage of the tool are described in the documentation.
Year
DOI
Venue
2009
10.1093/bioinformatics/btp131
Bioinformatics
Keywords
Field
DocType
consistency-enhanced alignment graph,insert sequencing,multi-read alignment algorithm,reference-guided sequence assembly,sound multi-read alignment,consistency-based consensus algorithm,comparable program,variation analysis,versatile consensus tool,consensus program,high-coverage data,accurate genome assembly,algorithms,computational biology,sequence alignment,computer science,internet
Sequence alignment,Genome,Data mining,Hybrid genome assembly,Consensus algorithm,Computer science,Bioinformatics,Documentation,Sequence Read Archive,Sequence assembly,The Internet
Journal
Volume
Issue
ISSN
25
9
1367-4811
Citations 
PageRank 
References 
8
0.61
13
Authors
7
Name
Order
Citations
PageRank
Tobias Rausch126218.00
Sergey Koren211511.73
Gennady Denisov3425.44
David Weese425217.79
Anne-katrin Emde51016.06
Andreas Döring619519.38
Knut Reinert71020105.87