Error correction and diversity analysis of population mixtures determined by NGS

Graham R. Wood*, Nigel J. Burroughs, David J. Evans, Eugene V. Ryabov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The impetus for this work was the need to analyse nucleotide diversity in a viral mix taken from honeybees. 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. The error correction method is statistically based and 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. The methods are illustrated using honeybee viral samples. 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.

Original languageEnglish
Article number645
Number of pages17
JournalPeerJ
Volume2
DOIs
Publication statusPublished - 13 Nov 2014

Keywords

  • Calibration
  • Error correction
  • Honeybee
  • Metagenome
  • Nucleotide diversity
  • Standard sample
  • Viral mix

Fingerprint

Dive into the research topics of 'Error correction and diversity analysis of population mixtures determined by NGS'. Together they form a unique fingerprint.

Cite this