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A methodology designed to take advantage of a high coverage by independently assembling disjoint subsets of reads, combining the assemblies of the subsets, and finally re-assembling the combined contigs along with the original reads. By using HGA method, there is a significant improvement in the assembly quality, based on N50 and corrected N50 metrics, using different assemblers on different genomes. HGA applies hierarchical approach where the assembly process starts with lower coverage assembly to get more corrected but shorter contigs results, then assembling these contigs with all reads again to gain longer contigs results.

Software type:
Package
Interface:
Command line interface
Restrictions to use:
None
Biological technology:
Illumina
Operating system:
Unix/Linux
Programming languages:
Python
License:
GNU General Public License version 3.0
Computer skills:
Advanced
Version:
1.0.0
Stability:
Stable
Requirements:
SPAdes v3.0.0, Velvet v1.2.10
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Institution(s)

Computer Science & Engineering Department, University of Connecticut, Storrs, CT, USA

Funding source(s)

This work has been partially supported by Agricud Food Research Initiative Competitive Grant no. 201167016-30331 from the USDA National Institute of Food and Agriculture.

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