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Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts

Overview of attention for article published in Genome Biology, May 2016
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
3 blogs
twitter
73 X users
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
107 Dimensions

Readers on

mendeley
364 Mendeley
citeulike
3 CiteULike
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Title
Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
Published in
Genome Biology, May 2016
DOI 10.1186/s13059-016-0970-8
Pubmed ID
Authors

Vasilis Ntranos, Govinda M. Kamath, Jesse M. Zhang, Lior Pachter, David N. Tse

Abstract

Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling, which limits their scope and generality. We propose a novel method that compares and clusters cells based on their transcript-compatibility read counts rather than on the transcript or gene quantifications used in standard analysis pipelines. In the reanalysis of two landmark yet disparate single-cell RNA-seq datasets, we show that our method is up to two orders of magnitude faster than previous approaches, provides accurate and in some cases improved results, and is directly applicable to data from a wide variety of assays.

X Demographics

X Demographics

The data shown below were collected from the profiles of 73 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 364 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 2%
United Kingdom 2 <1%
Denmark 2 <1%
Brazil 1 <1%
Sweden 1 <1%
Canada 1 <1%
Taiwan 1 <1%
Argentina 1 <1%
Germany 1 <1%
Other 4 1%
Unknown 342 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 98 27%
Researcher 97 27%
Student > Bachelor 31 9%
Student > Master 30 8%
Student > Postgraduate 18 5%
Other 48 13%
Unknown 42 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 104 29%
Biochemistry, Genetics and Molecular Biology 97 27%
Computer Science 38 10%
Mathematics 14 4%
Medicine and Dentistry 14 4%
Other 44 12%
Unknown 53 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 59. 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 18 August 2023.
All research outputs
#716,532
of 25,371,288 outputs
Outputs from Genome Biology
#463
of 4,467 outputs
Outputs of similar age
#13,794
of 351,831 outputs
Outputs of similar age from Genome Biology
#10
of 84 outputs
Altmetric has tracked 25,371,288 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 4,467 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 well, scoring higher than 89% 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 351,831 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 96% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.