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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
3 X users
patent
1 patent
wikipedia
1 Wikipedia page

Citations

dimensions_citation
391 Dimensions

Readers on

mendeley
405 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 405 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
United Kingdom 3 <1%
Germany 2 <1%
Brazil 2 <1%
Netherlands 1 <1%
France 1 <1%
Portugal 1 <1%
Argentina 1 <1%
China 1 <1%
Other 5 1%
Unknown 379 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 119 29%
Researcher 81 20%
Student > Master 55 14%
Student > Bachelor 26 6%
Student > Postgraduate 20 5%
Other 54 13%
Unknown 50 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 162 40%
Biochemistry, Genetics and Molecular Biology 65 16%
Computer Science 35 9%
Environmental Science 24 6%
Immunology and Microbiology 14 3%
Other 37 9%
Unknown 68 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 28 June 2022.
All research outputs
#1,515,748
of 25,373,627 outputs
Outputs from BMC Genomics
#273
of 11,244 outputs
Outputs of similar age
#13,610
of 287,026 outputs
Outputs of similar age from BMC Genomics
#6
of 186 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 97% 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 287,026 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 95% of its contemporaries.
We're also able to compare this research output to 186 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 96% of its contemporaries.