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The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Error filtering, pair assembly and error correction for next-generation sequencing reads

Open access
Edgar, Robert C., Flyvbjerg, Henrik·2015·Bioinformatics

Abstract

Motivation: Next-generation sequencing produces vast amounts of data with errors that are difficult to distinguish from true biological variation when coverage is low. Results: We demonstrate large reductions in error frequencies, especially for high-error-rate reads, by three independent means: (i) filtering reads according to their expected number of errors, (ii) assembling overlapping read pairs and (iii) for amplicon reads, by exploiting unique sequence abundances to perform error correction. We also show that most published paired read assemblers calculate incorrect posterior quality scores. Availability and implementation: These methods are implemented in the USEARCH package. Binaries are freely available at http://drive5.com/usearch. Contact: robert@drive5.com Supplementary information: Supplementary data are available at Bioinformatics online.

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Cites

Show all 8 references

Research works printed but not linked: 14

  1. Bokulich, 2013, Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing, Nat. Methods, 10, 57, 10.1038/nmeth.2276 · DOI · Paper page
  2. Edgar, 2010, Search and clustering orders of magnitude faster than BLAST, Bioinformatics, 26, 2460, 10.1093/bioinformatics/btq461 · DOI · Paper page
  3. Edgar, 2013, UPARSE: highly accurate OTU sequences from microbial amplicon reads, Nat. Methods, 10, 996, 10.1038/nmeth.2604 · DOI · Paper page
  4. Edgar, 2011, UCHIME improves sensitivity and speed of chimera detection, Bioinformatics, 27, 2194, 10.1093/bioinformatics/btr381 · DOI · Paper page
  5. Glenn, 2011, Field guide to next-generation DNA sequencers, Mol. Ecol. Resour., 11, 759, 10.1111/j.1755-0998.2011.03024.x · DOI · Paper page
  6. Haas, 2011, Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons, Genome Res., 494, 10.1101/gr.112730.110 · DOI · Paper page
  7. Kozich, 2013, Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq illumina sequencing platform, Appl. Environ. Microbiol., 79, 5112, 10.1128/AEM.01043-13 · DOI · Paper page
  8. Le Cam, 1960, An approximation theorem for the Poisson binomial distribution, Pacific J. Math., 10, 1181, 10.2140/pjm.1960.10.1181 · DOI · Paper page
  9. Quince, 2009, Accurate determination of microbial diversity from 454 pyrosequencing data, Nat. Methods, 6, 639, 10.1038/nmeth.1361 · DOI · Paper page
  10. Quince, 2011, Removing noise from pyrosequenced amplicons, BMC Bioinformatics, 12, 38, 10.1186/1471-2105-12-38 · DOI · Paper page
  11. Reeder, 2010, Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions, Nat. Methods, 7, 668, 10.1038/nmeth0910-668b · DOI · Paper page
  12. Reveillaud, 2014, Host-specificity among abundant and rare taxa in the sponge microbiome, ISME J., 8, 1198, 10.1038/ismej.2013.227 · DOI · Paper page
  13. Wang, 1993, On the number of successes in independent trials, Stat. Sin., 3, 295
  14. Zhang, 2014, PEAR: a fast and accurate Illumina paired-end read merger, Bioinformatics, 30, 614, 10.1093/bioinformatics/btt593 · DOI · Paper page

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Metadata

Authors
Edgar, R. C., & Flyvbjerg, H.
Venue
Bioinformatics
Published
2015-07-02
Volume
31
Issue
21
Pages
3476-3482
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2162667876
Cited by
1,275
References
8
FWCI
28.05
Type
journal article
Language
en
Open access
bronze

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Edgar, R. C., & Flyvbjerg, H. (2015). Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics. https://doi.org/10.1093/bioinformatics/btv401

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