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Error correction and diversity analysis of population mixtures determined by NGS

, , ,
1 Systems Biology, University of Warwick, UK, Coventry, United Kingdom
2 Centre for Systems Biology, University of Warwick, Coventry, United Kingdom
3 School of Life Sciences, University of Warwick, Coventry, United Kingdon
DOI
10.7287/peerj.preprints.441v1
Published
Accepted
Subject Areas
Biodiversity, Bioinformatics, Computational Biology, Genetics, Mathematical Biology
Keywords
calibration, error correction, metagenome, nucleotide diversity, honeybee, viral mix, standard sample
Copyright
© 2014 Wood et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Wood GR, Burroughs N, Evans DJ, Ryabov EV. 2014. Error correction and diversity analysis of population mixtures determined by NGS. PeerJ PrePrints 2:e441v1

Abstract

The impetus for this work was the need to analyse nucleotide diversity in a viral mix taken from honeybees; the methods are illustrated using honeybee viral samples. The paper has two findings. First, a method for correction of next generation sequencing error in the distribution of nucleotides at a site is developed. Second, a package of methods for assessment of nucleotide diversity is assembled. A statistically based error correction method is presented, which works at the level of the nucleotide distribution rather than the level of individual nucleotides. The method relies on an error model and a sample of known viral genotypes that is used for model calibration. A compendium of existing and new diversity analysis tools is also presented, allowing hypotheses about diversity and mean diversity to be tested and associated confidence intervals to be calculated. Software in both Excel and Matlab and a guide are available at http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/, the Warwick University Systems Biology Centre software download site.

Author Comment

This preprint is currently submitted to PeerJ for review.

Additional Information

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Graham R Wood conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables.

Nigel Burroughs conceived and designed the experiments, contributed reagents/materials/analysis tools, reviewed drafts of the paper.

David J Evans conceived and designed the experiments, contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Eugene V Ryabov conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper.

DNA Deposition

The following information was supplied regarding the deposition of DNA sequences:

EBI SRA study accession PRJEB5249, ERS395182 EBI SRA study accession PRJEB5249, ERS395180

NCBI Accession Nos. HM067437 and HM067438

Data Deposition

The following information was supplied regarding the deposition of related data:

EBI SRA study accession PRJEB5249, ERS395182 EBI SRA study accession PRJEB5249, ERS395180

NCBI Accession Nos. HM067437 and HM067438

Funding

This work was supported by the Biotechnology and Biological Sciences Research Council, the Department for Environment, Food and Rural Affairs, the Natural Environment Research Council, the Scottish Government and the Wellcome Trust, under the Insect Pollinators Initiative [grant number BBI0008281]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Error correction and diversity analysis of population mixtures determined by NGS
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