↓ Skip to main content

scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets

Overview of attention for article published in BMC Genomics, January 2021
Altmetric Badge

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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
20 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
12 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets
Published in
BMC Genomics, January 2021
DOI 10.1186/s12864-020-07334-y
Pubmed ID
Authors

Hongyu Liu, N. M. Prashant, Liam F. Spurr, Pavlos Bousounis, Nawaf Alomran, Helen Ibeawuchi, Justin Sein, Piotr Słowiński, Krasimira Tsaneva-Atanasova, Anelia Horvath

Twitter Demographics

The data shown below were collected from the profiles of 20 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 17%
Student > Bachelor 2 17%
Student > Ph. D. Student 1 8%
Student > Master 1 8%
Researcher 1 8%
Other 1 8%
Unknown 4 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 42%
Computer Science 1 8%
Agricultural and Biological Sciences 1 8%
Unknown 5 42%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 15 May 2021.
All research outputs
#2,649,168
of 19,338,160 outputs
Outputs from BMC Genomics
#1,087
of 9,772 outputs
Outputs of similar age
#89,871
of 452,694 outputs
Outputs of similar age from BMC Genomics
#74
of 669 outputs
Altmetric has tracked 19,338,160 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,772 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 88% 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 452,694 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 80% of its contemporaries.
We're also able to compare this research output to 669 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.