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Meta-IDBA: a de Novo assembler for metagenomic data

Authors: Peng, Y; Chin, FYL; Yiu, SM; Leung, HCM;

Meta-IDBA: a de Novo assembler for metagenomic data

Abstract

Abstract Motivation: Next-generation sequencing techniques allow us to generate reads from a microbial environment in order to analyze the microbial community. However, assembling of a set of mixed reads from different species to form contigs is a bottleneck of metagenomic research. Although there are many assemblers for assembling reads from a single genome, there are no assemblers for assembling reads in metagenomic data without reference genome sequences. Moreover, the performances of these assemblers on metagenomic data are far from satisfactory, because of the existence of common regions in the genomes of subspecies and species, which make the assembly problem much more complicated. Results: We introduce the Meta-IDBA algorithm for assembling reads in metagenomic data, which contain multiple genomes from different species. There are two core steps in Meta-IDBA. It first tries to partition the de Bruijn graph into isolated components of different species based on an important observation. Then, for each component, it captures the slight variants of the genomes of subspecies from the same species by multiple alignments and represents the genome of one species, using a consensus sequence. Comparison of the performances of Meta-IDBA and existing assemblers, such as Velvet and Abyss for different metagenomic datasets shows that Meta-IDBA can reconstruct longer contigs with similar accuracy. Availability: Meta-IDBA toolkit is available at our website http://www.cs.hku.hk/~alse/metaidba. Contact: chin@cs.hku.hk

Country
China (People's Republic of)
Related Organizations
Keywords

Metagenomics - methods, Escherichia coli - classification - genetics - isolation and purification, Escherichia coli, Ismb/Eccb 2011 Proceedings Papers Committee July 17 to July 19, 2011, Vienna, Austria, Metagenomics, Sequence Analysis, DNA, Algorithms, Genome, Bacterial, Software

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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!
291
Top 1%
Top 1%
Top 1%
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