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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SCeQTL: an R package for identifying eQTL from single-cell parallel sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, May 2020
|
| DOI | 10.1186/s12859-020-3534-6 |
| Pubmed ID | |
| Authors |
Yue Hu, Xi Xi, Qian Yang, Xuegong Zhang |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 13% |
| Austria | 1 | 13% |
| India | 1 | 13% |
| Italy | 1 | 13% |
| United Kingdom | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 75% |
| Scientists | 2 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 57 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 19% |
| Student > Ph. D. Student | 10 | 18% |
| Student > Bachelor | 5 | 9% |
| Student > Master | 5 | 9% |
| Student > Doctoral Student | 3 | 5% |
| Other | 8 | 14% |
| Unknown | 15 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 33% |
| Computer Science | 7 | 12% |
| Medicine and Dentistry | 6 | 11% |
| Agricultural and Biological Sciences | 5 | 9% |
| Unspecified | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 13 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 14 May 2020.
All research outputs
#6,883,767
of 24,051,764 outputs
Outputs from BMC Bioinformatics
#2,549
of 7,495 outputs
Outputs of similar age
#139,966
of 388,786 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 111 outputs
Altmetric has tracked 24,051,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,495 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 64% 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 388,786 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.