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dc.contributor.authorArcher, John
dc.contributor.authorBaillie, Greg
dc.contributor.authorWatson, Simon
dc.contributor.authorKellam, Paul
dc.contributor.authorRambaut, Andrew
dc.contributor.authorRobertson, David
dc.date.accessioned2018-01-11T03:37:46Z
dc.date.available2018-01-11T03:37:46Z
dc.date.issued2012
dc.date.modified2014-08-19T04:42:42Z
dc.identifier.issn1471-2105
dc.identifier.doi10.1186/1471-2105-13-47
dc.identifier.urihttp://hdl.handle.net/10072/62525
dc.description.abstractBackground Next generation sequencing provides detailed insight into the variation present within viral populations, introducing the possibility of treatment strategies that are both reactive and predictive. Current software tools, however, need to be scaled up to accommodate for high-depth viral data sets, which are often temporally or spatially linked. In addition, due to the development of novel sequencing platforms and chemistries, each with implicit strengths and weaknesses, it will be helpful for researchers to be able to routinely compare and combine data sets from different platforms/chemistries. In particular, error associated with a specific sequencing process must be quantified so that true biological variation may be identified. Results Segminator II was developed to allow for the efficient comparison of data sets derived from different sources. We demonstrate its usage by comparing large data sets from 12 influenza H1N1 samples sequenced on both the 454 Life Sciences and Illumina platforms, permitting quantification of platform error. For mismatches median error rates at 0.10 and 0.12%, respectively, suggested that both platforms performed similarly. For insertions and deletions median error rates within the 454 data (at 0.3 and 0.2%, respectively) were significantly higher than those within the Illumina data (0.004 and 0.006%, respectively). In agreement with previous observations these higher rates were strongly associated with homopolymeric stretches on the 454 platform. Outside of such regions both platforms had similar indel error profiles. Additionally, we apply our software to the identification of low frequency variants. Conclusion We have demonstrated, using Segminator II, that it is possible to distinguish platform specific error from biological variation using data derived from two different platforms. We have used this approach to quantify the amount of error present within the 454 and Illumina platforms in relation to genomic location as well as location on the read. Given that next generation data is increasingly important in the analysis of drug-resistance and vaccine trials, this software will be useful to the pathogen research community. A zip file containing the source code and jar file is freely available for download from http://www.bioinf.manchester.ac.uk/segminator/ webcite.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherBioMed Central
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom47-1
dc.relation.ispartofpageto47-11
dc.relation.ispartofjournalBMC Bioinformatics
dc.relation.ispartofvolume13
dc.rights.retentionY
dc.subject.fieldofresearchBiological Sciences not elsewhere classified
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchBiological Sciences
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchcode069999
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode06
dc.subject.fieldofresearchcode08
dc.titleAnalysis of high-depth sequence data for studying viral diversity: a comparison of next generation sequencing platforms using Segminator II
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by/2.0
dc.description.versionVersion of Record (VoR)
gro.description.notepublicPage numbers are not for citation purposes. Instead, this article has the unique article number of 47.
gro.rights.copyright© 2012 Archer et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorBaillie, Greg


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