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Pollux: platform independent error correction of single and mixed genomes

Overview of attention for article published in BMC Bioinformatics, January 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
14 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
83 Mendeley
citeulike
2 CiteULike
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Title
Pollux: platform independent error correction of single and mixed genomes
Published in
BMC Bioinformatics, January 2015
DOI 10.1186/s12859-014-0435-6
Pubmed ID
Authors

Eric Marinier, Daniel G Brown, Brendan J McConkey

Abstract

BackgroundSecond-generation sequencers generate millions of relatively short, but error-prone, reads. These errors make sequence assembly and other downstream projects more challenging. Correcting these errors improves the quality of assemblies and projects which benefit from error-free reads.ResultsWe have developed a general-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.ConclusionsPollux is highly effective at correcting errors across platforms, and is consistently able to perform as well or better than currently available error correction software. Pollux provides general-purpose error correction and may be used in applications with or without assembly.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Italy 1 1%
Korea, Republic of 1 1%
Norway 1 1%
Sweden 1 1%
United Kingdom 1 1%
France 1 1%
Unknown 74 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 39%
Student > Ph. D. Student 13 16%
Student > Master 12 14%
Student > Bachelor 5 6%
Professor 4 5%
Other 12 14%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 40%
Biochemistry, Genetics and Molecular Biology 19 23%
Computer Science 10 12%
Environmental Science 4 5%
Immunology and Microbiology 2 2%
Other 5 6%
Unknown 10 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2015.
All research outputs
#1,819,030
of 11,342,664 outputs
Outputs from BMC Bioinformatics
#868
of 4,199 outputs
Outputs of similar age
#48,729
of 253,037 outputs
Outputs of similar age from BMC Bioinformatics
#29
of 156 outputs
Altmetric has tracked 11,342,664 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,199 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 253,037 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.