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A benchmark of batch-effect correction methods for single-cell RNA sequencing data

Overview of attention for article published in Genome Biology (Online Edition), January 2020
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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)

Mentioned by

blogs
1 blog
twitter
174 tweeters
facebook
1 Facebook page
f1000
1 research highlight platform

Citations

dimensions_citation
317 Dimensions

Readers on

mendeley
611 Mendeley
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Title
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Published in
Genome Biology (Online Edition), January 2020
DOI 10.1186/s13059-019-1850-9
Pubmed ID
Authors

Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen

Twitter Demographics

The data shown below were collected from the profiles of 174 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 611 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 611 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 130 21%
Researcher 109 18%
Student > Master 60 10%
Student > Bachelor 50 8%
Student > Doctoral Student 29 5%
Other 65 11%
Unknown 168 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 184 30%
Agricultural and Biological Sciences 72 12%
Computer Science 45 7%
Medicine and Dentistry 32 5%
Immunology and Microbiology 27 4%
Other 70 11%
Unknown 181 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 100. 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 April 2022.
All research outputs
#311,874
of 21,200,954 outputs
Outputs from Genome Biology (Online Edition)
#202
of 4,015 outputs
Outputs of similar age
#8,200
of 365,099 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 21,200,954 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,015 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one has done particularly well, scoring higher than 94% 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 365,099 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them