Evidence map›Paper›PMID 29453452›Full record

ArticleScientific reports2018

Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias.

Raga Krishnakumar, Anupama Sinha, Sara W Bird, Harikrishnan Jayamohan, Harrison S Edwards, Joseph S Schoeniger, Kamlesh D Patel, Steven S Branda, Michael S Bartsch

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
–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

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Raga KrishnakumarSystems Biology, Sandia National Laboratories, Livermore, CA, USA. rkrishn@sandia.gov.
Anupama SinhaSystems Biology, Sandia National Laboratories, Livermore, CA, USA.
Sara W BirdBiotechnology and Bioengineering, Sandia National Laboratories, Livermore, CA, USA.
Harikrishnan JayamohanAdvanced Systems Engineering & Deployment, Sandia National Laboratories, Livermore, CA, USA.
Harrison S EdwardsAdvanced Systems Engineering & Deployment, Sandia National Laboratories, Livermore, CA, USA.
Joseph S SchoenigerSystems Biology, Sandia National Laboratories, Livermore, CA, USA.
Kamlesh D PatelAdvanced Systems Engineering & Deployment, Sandia National Laboratories, Livermore, CA, USA.
Steven S BrandaBiomass Science and Conversion Technology, Sandia National Laboratories, Livermore, CA, USA.
Michael S BartschAdvanced Systems Engineering & Deployment, Sandia National Laboratories, Livermore, CA, USA. mbarts@sandia.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.

Indexed as

NanoporesAlgorithmsGenomicsNucleotidesSequence Analysis, DNAStochastic ProcessesNucleotides

Identifiers

PMID29453452
PMCPMC5816649

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.