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CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data

Overview of attention for article published in Genome Biology, March 2017
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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 (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
25 X users
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
431 Dimensions

Readers on

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374 Mendeley
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Title
CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data
Published in
Genome Biology, March 2017
DOI 10.1186/s13059-017-1188-0
Pubmed ID
Authors

Peijie Lin, Michael Troup, Joshua W. K. Ho

Abstract

Most existing dimensionality reduction and clustering packages for single-cell RNA-seq (scRNA-seq) data deal with dropouts by heavy modeling and computational machinery. Here, we introduce CIDR (Clustering through Imputation and Dimensionality Reduction), an ultrafast algorithm that uses a novel yet very simple implicit imputation approach to alleviate the impact of dropouts in scRNA-seq data in a principled manner. Using a range of simulated and real data, we show that CIDR improves the standard principal component analysis and outperforms the state-of-the-art methods, namely t-SNE, ZIFA, and RaceID, in terms of clustering accuracy. CIDR typically completes within seconds when processing a data set of hundreds of cells and minutes for a data set of thousands of cells. CIDR can be downloaded at https://github.com/VCCRI/CIDR .

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 374 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
United Kingdom 2 <1%
Denmark 1 <1%
Mexico 1 <1%
Japan 1 <1%
Poland 1 <1%
Unknown 364 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 101 27%
Researcher 67 18%
Student > Bachelor 29 8%
Student > Master 28 7%
Student > Doctoral Student 21 6%
Other 56 15%
Unknown 72 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 93 25%
Agricultural and Biological Sciences 71 19%
Computer Science 58 16%
Medicine and Dentistry 14 4%
Mathematics 13 3%
Other 41 11%
Unknown 84 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 17 November 2019.
All research outputs
#2,116,579
of 25,382,440 outputs
Outputs from Genome Biology
#1,779
of 4,468 outputs
Outputs of similar age
#39,372
of 322,922 outputs
Outputs of similar age from Genome Biology
#36
of 64 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 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 gotten more attention than average, scoring higher than 60% 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 322,922 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.