Graph accordance of next-generation sequence assemblies

Guohui Yao(Washington University in St. Louis), Ye Liang(Washington University in St. Louis), Hongyu Gao(Washington University in St. Louis), Patrick Minx(Washington University in St. Louis), Wesley C. Warren(Washington University in St. Louis), George M. Weinstock(Washington University in St. Louis)
Bioinformatics
October 23, 2011
Cited by 54Open Access
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Abstract

MOTIVATION: 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. AVAILABILITY: GAA is implemented in OO perl and is available here: http://sourceforge.net/projects/gaa-wugi/. CONTACT: lye@genome.wustl.edu


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