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DE-kupl: exhaustive capture of biological variation in RNA-seq data through k-mer decomposition

Overview of attention for article published in Genome Biology, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
2 blogs
twitter
137 X users
f1000
1 research highlight platform

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
140 Mendeley
citeulike
1 CiteULike
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Title
DE-kupl: exhaustive capture of biological variation in RNA-seq data through k-mer decomposition
Published in
Genome Biology, December 2017
DOI 10.1186/s13059-017-1372-2
Pubmed ID
Authors

Jérôme Audoux, Nicolas Philippe, Rayan Chikhi, Mikaël Salson, Mélina Gallopin, Marc Gabriel, Jérémy Le Coz, Emilie Drouineau, Thérèse Commes, Daniel Gautheret

Abstract

We introduce a k-mer-based computational protocol, DE-kupl, for capturing local RNA variation in a set of RNA-seq libraries, independently of a reference genome or transcriptome. DE-kupl extracts all k-mers with differential abundance directly from the raw data files. This enables the retrieval of virtually all variation present in an RNA-seq data set. This variation is subsequently assigned to biological events or entities such as differential long non-coding RNAs, splice and polyadenylation variants, introns, repeats, editing or mutation events, and exogenous RNA. Applying DE-kupl to human RNA-seq data sets identified multiple types of novel events, reproducibly across independent RNA-seq experiments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 137 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Unknown 138 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 31%
Student > Ph. D. Student 27 19%
Student > Master 12 9%
Student > Bachelor 9 6%
Other 6 4%
Other 18 13%
Unknown 24 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 29%
Biochemistry, Genetics and Molecular Biology 37 26%
Computer Science 16 11%
Engineering 7 5%
Veterinary Science and Veterinary Medicine 2 1%
Other 9 6%
Unknown 28 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 83. 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 November 2018.
All research outputs
#510,636
of 25,396,120 outputs
Outputs from Genome Biology
#287
of 4,470 outputs
Outputs of similar age
#11,810
of 448,958 outputs
Outputs of similar age from Genome Biology
#8
of 48 outputs
Altmetric has tracked 25,396,120 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 93% 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 448,958 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 97% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.