Evidence map›Paper›PMID 32078666›Full record

ArticlePloS one2020

Comparison of sequencing methods and data processing pipelines for whole genome sequencing and minority single nucleotide variant (mSNV) analysis during an influenza A/H5N8 outbreak.

Marjolein J Poen, Anne Pohlmann, Clara Amid, Theo M Bestebroer, Sharon M Brookes, Ian H Brown, Helen Everett, Claudia M E Schapendonk, Rachel D Scheuer, Saskia L Smits and 3 more

Abstract readComparative Study
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Improved influenza A whole-genome sequencing protocol.Frontiers in cellular and infection microbiology · 2024
    Article
  2. Review
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

13 authors.

Marjolein J PoenErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.ORCID 0000-0002-0390-3462
Anne PohlmannInstitute of Diagnostic Virology, Friedrich-Loeffler-Institute, Insel Riems, Germany.
Clara AmidEuropean Molecular Biology Laboratory (EMBL), European Bioinformatics Institute (EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Theo M BestebroerErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.
Sharon M BrookesAnimal and Plant Health Agency (APHA) - Weybridge, Addlestone, Surrey, United Kingdom.
Ian H BrownAnimal and Plant Health Agency (APHA) - Weybridge, Addlestone, Surrey, United Kingdom.
Helen EverettAnimal and Plant Health Agency (APHA) - Weybridge, Addlestone, Surrey, United Kingdom.
Claudia M E SchapendonkErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.
Rachel D ScheuerErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.
Saskia L SmitsErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.
Martin BeerInstitute of Diagnostic Virology, Friedrich-Loeffler-Institute, Insel Riems, Germany.
Ron A M FouchierErasmus MC, Department of Viroscience, Rotterdam, the Netherlands.
Richard J EllisAnimal and Plant Health Agency (APHA) - Weybridge, Addlestone, Surrey, United Kingdom.

Funding

NIAID NIH HHS HHSN272201400008C
6 · The paper itself

Abstract

As high-throughput sequencing technologies are becoming more widely adopted for analysing pathogens in disease outbreaks there needs to be assurance that the different sequencing technologies and approaches to data analysis will yield reliable and comparable results. Conversely, understanding where agreement cannot be achieved provides insight into the limitations of these approaches and also allows efforts to be focused on areas of the process that need improvement. This manuscript describes the next-generation sequencing of three closely related viruses, each analysed using different sequencing strategies, sequencing instruments and data processing pipelines. In order to determine the comparability of consensus sequences and minority (sub-consensus) single nucleotide variant (mSNV) identification, the biological samples, the sequence data from 3 sequencing platforms and the *.bam quality-trimmed alignment files of raw data of 3 influenza A/H5N8 viruses were shared. This analysis demonstrated that variation in the final result could be attributed to all stages in the process, but the most critical were the well-known homopolymer errors introduced by 454 sequencing, and the alignment processes in the different data processing pipelines which affected the consistency of mSNV detection. However, homopolymer errors aside, there was generally a good agreement between consensus sequences that were obtained for all combinations of sequencing platforms and data processing pipelines. Nevertheless, minority variant analysis will need a different level of careful standardization and awareness about the possible limitations, as shown in this study.

Indexed as

Polymorphism, Single NucleotideAnimalsDisease OutbreaksDucksGenome, ViralInfluenza A Virus, H5N8 SubtypeOrthomyxoviridae InfectionsRNA, ViralSequence Analysis, DNAWhole Genome SequencingRNA, Viral

Identifiers

PMID32078666
PMCPMC7032710

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.