Evidence map›Paper›PMID 25198770›Full record

ArticlePloS one2014

GABenchToB: a genome assembly benchmark tuned on bacteria and benchtop sequencers.

Sebastian Jünemann, Karola Prior, Andreas Albersmeier, Stefan Albaum, Jörn Kalinowski, Alexander Goesmann, Jens Stoye, Dag Harmsen

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

14 citing papers in PubMed.

  1. Article
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  9. A Primer on Infectious Disease Bacterial Genomics.Clinical microbiology reviews · 2016
    Review
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  12. Review
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  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Sebastian JünemannDepartment for Periodontology, University of Münster, Münster, Germany; Institute for Bioinformatics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
Karola PriorDepartment for Periodontology, University of Münster, Münster, Germany.
Andreas AlbersmeierTechnology Platform Genomics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
Stefan AlbaumBioinformatics Resource Facility, Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
Jörn KalinowskiTechnology Platform Genomics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
Alexander GoesmannBioinformatics and Systems Biology, Justus-Liebig-Univeristy Gießen, Gießen, Germany.
Jens StoyeInstitute for Bioinformatics, Center for Biotechnology, Bielefeld University, Bielefeld, Germany; Genome Informatics Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany.
Dag HarmsenDepartment for Periodontology, University of Münster, Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

De novo genome assembly is the process of reconstructing a complete genomic sequence from countless small sequencing reads. Due to the complexity of this task, numerous genome assemblers have been developed to cope with different requirements and the different kinds of data provided by sequencers within the fast evolving field of next-generation sequencing technologies. In particular, the recently introduced generation of benchtop sequencers, like Illumina's MiSeq and Ion Torrent's Personal Genome Machine (PGM), popularized the easy, fast, and cheap sequencing of bacterial organisms to a broad range of academic and clinical institutions. With a strong pragmatic focus, here, we give a novel insight into the line of assembly evaluation surveys as we benchmark popular de novo genome assemblers based on bacterial data generated by benchtop sequencers. Therefore, single-library assemblies were generated, assembled, and compared to each other by metrics describing assembly contiguity and accuracy, and also by practice-oriented criteria as for instance computing time. In addition, we extensively analyzed the effect of the depth of coverage on the genome assemblies within reasonable ranges and the k-mer optimization problem of de Bruijn Graph assemblers. Our results show that, although both MiSeq and PGM allow for good genome assemblies, they require different approaches. They not only pair with different assembler types, but also affect assemblies differently regarding the depth of coverage where oversampling can become problematic. Assemblies vary greatly with respect to contiguity and accuracy but also by the requirement on the computing power. Consequently, no assembler can be rated best for all preconditions. Instead, the given kind of data, the demands on assembly quality, and the available computing infrastructure determines which assembler suits best. The data sets, scripts and all additional information needed to replicate our results are freely available at ftp://ftp.cebitec.uni-bielefeld.de/pub/GABenchToB.

Indexed as

Genome, BacterialSoftwareAlgorithmsBacteriaBenchmarkingGenes, BacterialGenomicsHigh-Throughput Nucleotide SequencingSequence Analysis, DNA

Identifiers

PMID25198770
PMCPMC4157817

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.