SEQuel: improving the accuracy of genome assemblies.
BACKGROUND
Assemblies of next-generation sequencing (NGS) data, although accurate, still contain a substantial number of errors that need to be corrected after the assembly process. We develop SEQuel, a tool that corrects errors (i.e. insertions, deletions and substitution errors) in the assembled contigs. Fundamental to the algorithm behind SEQuel is the positional de Bruijn graph, a graph structure that models k-mers within reads while incorporating the approximate positions of reads into the model.


RESULTS
SEQuel reduced the number of small insertions and deletions in the assemblies of standard multi-cell Escherichia coli data by almost half, and corrected between 30% and 94% of the substitution errors. Further, we show SEQuel is imperative to improving single-cell assembly, which is inherently more challenging due to higher error rates and non-uniform coverage; over half of the small indels, and substitution errors in the single-cell assemblies were corrected. We apply SEQuel to the recently assembled Deltaproteobacterium SAR324 genome, which is the first bacterial genome with a comprehensive single-cell genome assembly, and make over 800 changes (insertions, deletions and substitutions) to refine this assembly.


BACKGROUND
SEQuel can be used as a post-processing step in combination with any NGS assembler and is freely available at http://bix.ucsd.edu/SEQuel/.
Bioinformatics Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA.
Roy
R
Ronen
Christina
C
Boucher
Hamidreza
H
Chitsaz
Pavel
P
Pevzner
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D020451:Contig Mapping; D004926:Escherichia coli / Q000235:genetics; D016680:Genome, Bacterial; D054643:INDEL Mutation; D017422:Sequence Analysis, DNA / Q000379:methods*