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Profiling tissue-resident T cell repertoires by RNA sequencing

Overview of attention for article published in Genome Medicine, November 2015
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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 (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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29 X users
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1 Facebook page

Citations

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85 Dimensions

Readers on

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209 Mendeley
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2 CiteULike
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Title
Profiling tissue-resident T cell repertoires by RNA sequencing
Published in
Genome Medicine, November 2015
DOI 10.1186/s13073-015-0248-x
Pubmed ID
Authors

Scott D. Brown, Lisa A. Raeburn, Robert A. Holt

Abstract

Deep sequencing of recombined T cell receptor (TCR) genes and transcripts has provided a view of T cell repertoire diversity at an unprecedented resolution. Beyond profiling peripheral blood, analysis of tissue-resident T cells provides further insight into immune-related diseases. We describe the extraction of TCR sequence information directly from RNA-sequencing data from 6738 tumor and 604 control tissues, with a typical yield of 1 TCR per 10 million reads. This method circumvents the need for PCR amplification of the TCR template and provides TCR information in the context of global gene expression, allowing integrated analysis of extensive RNA-sequencing data resources.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 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 209 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
South Africa 1 <1%
Canada 1 <1%
Australia 1 <1%
Unknown 202 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 58 28%
Student > Ph. D. Student 39 19%
Student > Master 20 10%
Student > Bachelor 18 9%
Other 14 7%
Other 30 14%
Unknown 30 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 30%
Biochemistry, Genetics and Molecular Biology 48 23%
Immunology and Microbiology 26 12%
Medicine and Dentistry 16 8%
Computer Science 8 4%
Other 13 6%
Unknown 35 17%
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 19 November 2019.
All research outputs
#2,191,991
of 25,658,139 outputs
Outputs from Genome Medicine
#476
of 1,605 outputs
Outputs of similar age
#35,252
of 397,008 outputs
Outputs of similar age from Genome Medicine
#8
of 33 outputs
Altmetric has tracked 25,658,139 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 1,605 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one has gotten more attention than average, scoring higher than 70% 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 397,008 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 91% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.