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Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
- Source :
- Bioinformatics, Bioinformatics (Oxford, England), vol 34, iss 13
- Publication Year :
- 2018
- Publisher :
- Oxford University Press (OUP), 2018.
-
Abstract
- Motivation De novo genome assembly is a challenging computational problem due to the high repetitive content of eukaryotic genomes and the imperfections of sequencing technologies (i.e. sequencing errors, uneven sequencing coverage and chimeric reads). Several assembly tools are currently available, each of which has strengths and weaknesses in dealing with the trade-off between maximizing contiguity and minimizing assembly errors (e.g. mis-joins). To obtain the best possible assembly, it is common practice to generate multiple assemblies from several assemblers and/or parameter settings and try to identify the highest quality assembly. Unfortunately, often there is no assembly that both maximizes contiguity and minimizes assembly errors, so one has to compromise one for the other. Results The concept of assembly reconciliation has been proposed as a way to obtain a higher quality assembly by merging or reconciling all the available assemblies. While several reconciliation methods have been introduced in the literature, we have shown in one of our recent papers that none of them can consistently produce assemblies that are better than the assemblies provided in input. Here we introduce Novo&Stitch, a novel method that takes advantage of optical maps to accurately carry out assembly reconciliation (assuming that the assembled contigs are sufficiently long to be reliably aligned to the optical maps, e.g. 50 Kbp or longer). Experimental results demonstrate that Novo&Stitch can double the contiguity (N50) of the input assemblies without introducing mis-joins or reducing genome completeness. Availability and implementation Novo&Stitch can be obtained from https://github.com/ucrbioinfo/Novo_Stitch.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Bioinformatics
Phytophthora infestans
Computer science
Contiguity
Sequence assembly
Biochemistry
Genome
Mathematical Sciences
Contig Mapping
03 medical and health sciences
0302 clinical medicine
Information and Computing Sciences
Molecular Biology
Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
Contig
Vigna
Comparative and Functional Genomics
Eukaryota
DNA
Sequence Analysis, DNA
Biological Sciences
Computer Science Applications
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
Sequence Analysis
Algorithm
Software
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....9567f390d3169b119fe66d87fea24830