Evidence map›Paper›PMID 24564706›Full record

ArticleBMC bioinformatics2013

Finishing bacterial genome assemblies with Mix.

Hayssam Soueidan, Florence Maurier, Alexis Groppi, Pascal Sirand-Pugnet, Florence Tardy, Christine Citti, Virginie Dupuy, Macha Nikolski

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Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

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23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Genomic analysis reveals the potential for hydrocarbon degradation of Rhodopirellula sp. MGV isolated from a polluted Brazilian mangrove.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2021
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  9. Draft genome sequences ofStandards in genomic sciences · 2018
    Article
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  12. The draft genome of the hyperthermophilic archaeonStandards in genomic sciences · 2017
    Article
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  19. De novo meta-assembly of ultra-deep sequencing data.Bioinformatics (Oxford, England) · 2015
    Article
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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Hayssam Soueidan
Florence Maurier
Alexis Groppi
Pascal Sirand-Pugnet
Florence Tardy
Christine Citti
Virginie Dupuy
Macha Nikolski

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationAmong challenges that hamper reaping the benefits of genome assembly are both unfinished assemblies and the ensuing experimental costs. First, numerous software solutions for genome de novo assembly are available, each having its advantages and drawbacks, without clear guidelines as to how to choose among them. Second, these solutions produce draft assemblies that often require a resource intensive finishing phase.

methodsIn this paper we address these two aspects by developing Mix , a tool that mixes two or more draft assemblies, without relying on a reference genome and having the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a set of paths in the extension graph that maximizes the cumulative contig length.

resultsWe evaluate the performance of Mix on bacterial NGS data from the GAGE-B study and apply it to newly sequenced Mycoplasma genomes. Resulting final assemblies demonstrate a significant improvement in the overall assembly quality. In particular, Mix is consistent by providing better overall quality results even when the choice is guided solely by standard assembly statistics, as is the case for de novo projects. AVAILABILITY: Mix is implemented in Python and is available at https://github.com/cbib/MIX, novel data for our Mycoplasma study is available at http://services.cbib.u-bordeaux2.fr/mix/.

Indexed as

Genome, BacterialAlgorithmsHigh-Throughput Nucleotide SequencingMycoplasmaSequence Analysis, DNASoftware Design

Identifiers

PMID24564706
PMCPMC3851838

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.