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Bioinformatics
Article . 2012 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
Article
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Bioinformatics
Article . 2013
DBLP
Article . 2012
Data sources: DBLP
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Gossamer — a resource-efficient de novo assembler

Authors: Thomas C. Conway; Jeremy Wazny; Andrew J. Bromage; Justin Zobel; Bryan Beresford-Smith;

Gossamer — a resource-efficient de novo assembler

Abstract

Abstract Motivation: The de novo assembly of short read high-throughput sequencing data poses significant computational challenges. The volume of data is huge; the reads are tiny compared to the underlying sequence, and there are significant numbers of sequencing errors. There are numerous software packages that allow users to assemble short reads, but most are either limited to relatively small genomes (e.g. bacteria) or require large computing infrastructure or employ greedy algorithms and thus often do not yield high-quality results. Results: We have developed Gossamer, an implementation of the de Bruijn approach to assembly that requires close to the theoretical minimum of memory, but still allows efficient processing. Our results show that it is space efficient and produces high-quality assemblies. Availability: Gossamer is available for non-commercial use from http://www.genomics.csse.unimelb.edu.au/product-gossamer.php. Contact: tom.conway@nicta.com.au

Related Organizations
Keywords

Computational Biology, High-Throughput Nucleotide Sequencing, Sequence Analysis, DNA, Algorithms, Software

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
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