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xCell: digitally portraying the tissue cellular heterogeneity landscape

Overview of attention for article published in Genome Biology, 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 (96th percentile)

Mentioned by

blogs
2 blogs
twitter
164 X users
patent
40 patents
googleplus
1 Google+ user
f1000
1 research highlight platform

Citations

dimensions_citation
2697 Dimensions

Readers on

mendeley
1248 Mendeley
citeulike
1 CiteULike
Title
xCell: digitally portraying the tissue cellular heterogeneity landscape
Published in
Genome Biology, 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/ .

X Demographics

X Demographics

The data shown below were collected from the profiles of 164 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 1,248 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 <1%
United States 1 <1%
Austria 1 <1%
Unknown 1245 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 257 21%
Student > Ph. D. Student 238 19%
Student > Master 102 8%
Student > Bachelor 90 7%
Other 54 4%
Other 172 14%
Unknown 335 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 332 27%
Agricultural and Biological Sciences 192 15%
Medicine and Dentistry 118 9%
Immunology and Microbiology 70 6%
Computer Science 52 4%
Other 110 9%
Unknown 374 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 115. 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 13 February 2024.
All research outputs
#363,593
of 25,382,440 outputs
Outputs from Genome Biology
#170
of 4,468 outputs
Outputs of similar age
#7,453
of 335,891 outputs
Outputs of similar age from Genome Biology
#3
of 59 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 98th percentile: it's in the top 5% 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 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 335,891 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 59 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 96% of its contemporaries.