ArticleBioinformatics (Oxford, England)2013
Filtering duplicate reads from 454 pyrosequencing data.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 25 citations in OpenAlex.
- Differential performance of strategies for single-cell whole-genome amplification.Cell reports methods · 2025Article
- Comparative study of whole genome amplification and next generation sequencing performance of single cancer cells.Oncotarget · 2017Article
- Effect of method of deduplication on estimation of differential gene expression using RNA-seq.PeerJ · 2017Article
- Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution.Molecular biology and evolution · 2016Article
- Reply to Artifacts in the data of Hu et al.Nature genetics · 2016Article
- FlowClus: efficiently filtering and denoising pyrosequenced amplicons.BMC bioinformatics · 2015Article
- Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies.Bioinformatics and biology insights · 2015Review
- Simulating a population genomics data set using FlowSim.BMC research notes · 2014Article
- Analysis of plant microbe interactions in the era of next generation sequencing technologies.Frontiers in plant science · 2014Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationThroughout the recent years, 454 pyrosequencing has emerged as an efficient alternative to traditional Sanger sequencing and is widely used in both de novo whole-genome sequencing and metagenomics. Especially the latter application is extremely sensitive to sequencing errors and artificially duplicated reads. Both are common in 454 pyrosequencing and can create a strong bias in the estimation of diversity and composition of a sample. To date, there are several tools that aim to remove both sequencing noise and duplicates. Nevertheless, duplicate removal is often based on nucleotide sequences rather than on the underlying flow values, which contain additional information.
resultsWith the novel tool JATAC, we present an approach towards a more accurate duplicate removal by analysing flow values directly. Making use of previous findings on 454 flow data characteristics, we combine read clustering with Bayesian distance measures. Finally, we provide a benchmark with an existing algorithm. AVAILABILITY: JATAC is freely available under the General Public License from http://malde.org/ketil/jatac/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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