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BayesHammer: Bayesian clustering for error correction in single-cell sequencing

Overview of attention for article published in BMC Genomics, January 2013
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
5 tweeters
wikipedia
1 Wikipedia page

Readers on

mendeley
316 Mendeley
citeulike
4 CiteULike
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Title
BayesHammer: Bayesian clustering for error correction in single-cell sequencing
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-s1-s7
Pubmed ID
Authors

Sergey I Nikolenko, Anton I Korobeynikov, Max A Alekseyev

Abstract

Error correction of sequenced reads remains a difficult task, especially in single-cell sequencing projects with extremely non-uniform coverage. While existing error correction tools designed for standard (multi-cell) sequencing data usually come up short in single-cell sequencing projects, algorithms actually used for single-cell error correction have been so far very simplistic.We introduce several novel algorithms based on Hamming graphs and Bayesian subclustering in our new error correction tool BAYESHAMMER. While BAYESHAMMER was designed for single-cell sequencing, we demonstrate that it also improves on existing error correction tools for multi-cell sequencing data while working much faster on real-life datasets. We benchmark BAYESHAMMER on both k-mer counts and actual assembly results with the SPADES genome assembler.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 316 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 3%
United Kingdom 3 <1%
Germany 2 <1%
Brazil 2 <1%
Argentina 1 <1%
Netherlands 1 <1%
Turkey 1 <1%
France 1 <1%
China 1 <1%
Other 5 2%
Unknown 289 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 33%
Researcher 70 22%
Student > Master 44 14%
Student > Postgraduate 18 6%
Student > Bachelor 17 5%
Other 39 12%
Unknown 24 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 151 48%
Biochemistry, Genetics and Molecular Biology 51 16%
Computer Science 30 9%
Environmental Science 19 6%
Immunology and Microbiology 11 3%
Other 24 8%
Unknown 30 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 05 October 2013.
All research outputs
#305,714
of 5,036,908 outputs
Outputs from BMC Genomics
#171
of 4,592 outputs
Outputs of similar age
#7,356
of 93,324 outputs
Outputs of similar age from BMC Genomics
#7
of 162 outputs
Altmetric has tracked 5,036,908 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,592 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 96% 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 93,324 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.