Graph accordance of next-generation sequence assemblies.
BACKGROUND
No individual assembly algorithm addresses all the known limitations of assembling short-length sequences. Overall reduced sequence contig length is the major problem that challenges the usage of these assemblies. We describe an algorithm to take advantages of different assembly algorithms or sequencing platforms to improve the quality of next-generation sequence (NGS) assemblies.


RESULTS
The algorithm is implemented as a graph accordance assembly (GAA) program. The algorithm constructs an accordance graph to capture the mapping information between the target and query assemblies. Based on the accordance graph, the contigs or scaffolds of the target assembly can be extended, merged or bridged together. Extra constraints, including gap sizes, mate pairs, scaffold order and orientation, are explored to enforce those accordance operations in the correct context. We applied GAA to various chicken NGS assemblies and the results demonstrate improved contiguity statistics and higher genome and gene coverage.


BACKGROUND
GAA is implemented in OO perl and is available here: http://sourceforge.net/projects/gaa-wugi/.


BACKGROUND
lye@genome.wustl.edu
The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, MO 63108, USA.
Guohui
G
Yao
Liang
L
Ye
Hongyu
H
Gao
Patrick
P
Minx
Wesley C
WC
Warren
George M
GM
Weinstock
D000465:Algorithms; D000818:Animals; D002645:Chickens / Q000235:genetics; D020451:Contig Mapping; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*