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Diminishing return for increased Mappability with longer sequencing reads: implications of the k-mer distributions in the human genome

Overview of attention for article published in BMC Bioinformatics, January 2014
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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 (98th percentile)

Mentioned by

blogs
1 blog
twitter
32 X users

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
99 Mendeley
citeulike
3 CiteULike
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Title
Diminishing return for increased Mappability with longer sequencing reads: implications of the k-mer distributions in the human genome
Published in
BMC Bioinformatics, January 2014
DOI 10.1186/1471-2105-15-2
Pubmed ID
Authors

Wentian Li, Jan Freudenberg, Pedro Miramontes

Abstract

The amount of non-unique sequence (non-singletons) in a genome directly affects the difficulty of read alignment to a reference assembly for high throughput-sequencing data. Although a longer read is more likely to be uniquely mapped to the reference genome, a quantitative analysis of the influence of read lengths on mappability has been lacking. To address this question, we evaluate the k-mer distribution of the human reference genome. The k-mer frequency is determined for k ranging from 20 bp to 1000 bp.

X Demographics

X Demographics

The data shown below were collected from the profiles of 32 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 5%
United Kingdom 3 3%
India 1 1%
Brazil 1 1%
Russia 1 1%
Sweden 1 1%
Unknown 87 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 31%
Student > Ph. D. Student 20 20%
Student > Master 10 10%
Professor 7 7%
Student > Bachelor 7 7%
Other 19 19%
Unknown 5 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 42%
Biochemistry, Genetics and Molecular Biology 20 20%
Computer Science 12 12%
Medicine and Dentistry 5 5%
Physics and Astronomy 3 3%
Other 11 11%
Unknown 6 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 30 December 2021.
All research outputs
#1,291,904
of 24,001,212 outputs
Outputs from BMC Bioinformatics
#165
of 7,492 outputs
Outputs of similar age
#14,800
of 312,673 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 108 outputs
Altmetric has tracked 24,001,212 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 7,492 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 312,673 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 108 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 98% of its contemporaries.