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dc.contributor.authorShrestha, Ram K
dc.contributor.authorLubinsky, Baruch
dc.contributor.authorBansode, Vijay B
dc.contributor.authorMoinz, Mónica BJ
dc.contributor.authorMcCormack, Grace P
dc.contributor.authorTravers, Simon A
dc.date.accessioned2014-02-07T16:44:26Z
dc.date.available2014-02-07T16:44:26Z
dc.date.issued2014-01-30
dc.identifier.citationBMC Bioinformatics. 2014 Jan 30;15(1):33en_GB
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2105-15-33
dc.identifier.urihttp://hdl.handle.net/10147/312357
dc.description.abstractAbstract Background Many high throughput sequencing (HTS) approaches, such as the Roche/454 platform, produce sequences in which the quality of the sequence (as measured by a Phred-like quality scores) decreases linearly across a sequence read. Undertaking quality trimming of this data is essential to enable confidence in the results of subsequent downstream analysis. Here, we have developed a novel, highly sensitive and accurate approach (QTrim) for the quality trimming of sequence reads generated using the Roche/454 sequencing platform (or any platform with long reads that outputs Phred-like quality scores). Results The performance of QTrim was evaluated against all other available quality trimming approaches on both poor and high quality 454 sequence data. In all cases, QTrim appears to perform equally as well as the best other approach (PRINSEQ) with these two methods significantly outperforming all other methods. Further analysis of the trimmed data revealed that the novel trimming approach implemented in QTrim ensures that the prevalence of low quality bases in the resulting trimmed data is substantially lower than PRINSEQ or any of the other approaches tested. Conclusions QTrim is a novel, highly sensitive and accurate algorithm for the quality trimming of Roche/454 sequence reads. It is implemented both as an executable program that can be integrated with standalone sequence analysis pipelines and as a web-based application to enable individuals with little or no bioinformatics experience to quality trim their sequence data.
dc.language.isoenen
dc.subject.otherBIOINFORMATICSen_GB
dc.titleQTrim: a novel tool for the quality trimming of sequence reads generated using the Roche/454 sequencing platformen_GB
dc.language.rfc3066en
dc.rights.holderRam Krishna Shrestha et al.; licensee BioMed Central Ltd.
dc.description.statusPeer Reviewed
dc.date.updated2014-02-04T16:15:47Z
refterms.dateFOA2018-08-23T11:25:37Z
html.description.abstractAbstract Background Many high throughput sequencing (HTS) approaches, such as the Roche/454 platform, produce sequences in which the quality of the sequence (as measured by a Phred-like quality scores) decreases linearly across a sequence read. Undertaking quality trimming of this data is essential to enable confidence in the results of subsequent downstream analysis. Here, we have developed a novel, highly sensitive and accurate approach (QTrim) for the quality trimming of sequence reads generated using the Roche/454 sequencing platform (or any platform with long reads that outputs Phred-like quality scores). Results The performance of QTrim was evaluated against all other available quality trimming approaches on both poor and high quality 454 sequence data. In all cases, QTrim appears to perform equally as well as the best other approach (PRINSEQ) with these two methods significantly outperforming all other methods. Further analysis of the trimmed data revealed that the novel trimming approach implemented in QTrim ensures that the prevalence of low quality bases in the resulting trimmed data is substantially lower than PRINSEQ or any of the other approaches tested. Conclusions QTrim is a novel, highly sensitive and accurate algorithm for the quality trimming of Roche/454 sequence reads. It is implemented both as an executable program that can be integrated with standalone sequence analysis pipelines and as a web-based application to enable individuals with little or no bioinformatics experience to quality trim their sequence data.


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