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xCell: digitally portraying the tissue cellular heterogeneity landscape

Overview of attention for article published in Genome Biology (Online Edition), November 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 (93rd percentile)

Mentioned by

blogs
1 blog
twitter
173 tweeters
googleplus
1 Google+ user
f1000
1 research highlight platform

Citations

dimensions_citation
115 Dimensions

Readers on

mendeley
463 Mendeley
Title
xCell: digitally portraying the tissue cellular heterogeneity landscape
Published in
Genome Biology (Online Edition), November 2017
DOI 10.1186/s13059-017-1349-1
Pubmed ID
Authors

Dvir Aran, Zicheng Hu, Atul J. Butte

Abstract

Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/ .

Twitter Demographics

The data shown below were collected from the profiles of 173 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 463 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 <1%
Austria 1 <1%
Unknown 461 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 134 29%
Student > Ph. D. Student 101 22%
Unspecified 60 13%
Student > Master 45 10%
Student > Bachelor 31 7%
Other 92 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 143 31%
Agricultural and Biological Sciences 112 24%
Unspecified 74 16%
Medicine and Dentistry 42 9%
Computer Science 33 7%
Other 59 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 107. 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 07 August 2019.
All research outputs
#143,795
of 13,371,296 outputs
Outputs from Genome Biology (Online Edition)
#117
of 2,987 outputs
Outputs of similar age
#6,892
of 308,723 outputs
Outputs of similar age from Genome Biology (Online Edition)
#16
of 240 outputs
Altmetric has tracked 13,371,296 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 2,987 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.7. This one has done particularly well, scoring higher than 96% 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 308,723 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 240 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 93% of its contemporaries.