| Title |
eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs
|
|---|---|
| Published in |
bioRxiv, January 2020
|
| DOI | 10.1101/2020.01.29.924266 |
| Authors |
Nurlan Kerimov, James D. Hayhurst, Kateryna Peikova, Jonathan R. Manning, Peter Walter, Liis Kolberg, Marija Samoviča, Manoj Pandian Sakthivel, Ivan Kuzmin, Stephen J. Trevanion, Tony Burdett, Simon Jupp, Helen Parkinson, Irene Papatheodorou, Andrew Yates, Daniel R. Zerbino, Kaur Alasoo |
X Demographics
The data shown below were collected from the profiles of 95 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 16 | 17% |
| United Kingdom | 16 | 17% |
| Estonia | 9 | 9% |
| Germany | 3 | 3% |
| Belgium | 3 | 3% |
| Switzerland | 3 | 3% |
| Japan | 2 | 2% |
| Australia | 2 | 2% |
| Denmark | 1 | 1% |
| Other | 7 | 7% |
| Unknown | 33 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 49 | 52% |
| Members of the public | 44 | 46% |
| Practitioners (doctors, other healthcare professionals) | 2 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 30% |
| Student > Ph. D. Student | 15 | 19% |
| Student > Doctoral Student | 6 | 8% |
| Student > Master | 6 | 8% |
| Student > Bachelor | 5 | 6% |
| Other | 9 | 12% |
| Unknown | 13 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 29 | 38% |
| Agricultural and Biological Sciences | 15 | 19% |
| Neuroscience | 4 | 5% |
| Medicine and Dentistry | 3 | 4% |
| Computer Science | 2 | 3% |
| Other | 6 | 8% |
| Unknown | 18 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 58. 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 August 2021.
All research outputs
#751,142
of 25,748,735 outputs
Outputs from bioRxiv
#326
of 4,938 outputs
Outputs of similar age
#18,845
of 477,862 outputs
Outputs of similar age from bioRxiv
#15
of 88 outputs
Altmetric has tracked 25,748,735 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,938 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 28.8. This one has done particularly well, scoring higher than 93% 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 477,862 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 96% of its contemporaries.
We're also able to compare this research output to 88 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.