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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A highly sensitive and specific workflow for detecting rare copy-number variants from exome sequencing data
|
|---|---|
| Published in |
Genome Medicine, January 2020
|
| DOI | 10.1186/s13073-020-0712-0 |
| Pubmed ID | |
| Authors |
Ramakrishnan Rajagopalan, Jill R. Murrell, Minjie Luo, Laura K. Conlin |
X Demographics
The data shown below were collected from the profiles of 13 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 Kingdom | 3 | 23% |
| France | 1 | 8% |
| Israel | 1 | 8% |
| United States | 1 | 8% |
| Canada | 1 | 8% |
| Unknown | 6 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 62% |
| Members of the public | 5 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 92 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 22% |
| Student > Master | 14 | 15% |
| Student > Ph. D. Student | 13 | 14% |
| Other | 9 | 10% |
| Student > Postgraduate | 5 | 5% |
| Other | 5 | 5% |
| Unknown | 26 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 31 | 34% |
| Agricultural and Biological Sciences | 12 | 13% |
| Medicine and Dentistry | 10 | 11% |
| Computer Science | 4 | 4% |
| Engineering | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 29 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 22 February 2020.
All research outputs
#4,932,966
of 25,837,817 outputs
Outputs from Genome Medicine
#946
of 1,611 outputs
Outputs of similar age
#111,049
of 478,460 outputs
Outputs of similar age from Genome Medicine
#26
of 33 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 478,460 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 75% 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 is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.