| Title |
Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
|
|---|---|
| Published in |
Nature Genetics, November 2018
|
| DOI | 10.1038/s41588-018-0268-8 |
| Pubmed ID | |
| Authors |
Sarah M. Urbut, Gao Wang, Peter Carbonetto, Matthew Stephens |
X Demographics
The data shown below were collected from the profiles of 145 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 | 45 | 31% |
| United Kingdom | 9 | 6% |
| Germany | 8 | 6% |
| France | 4 | 3% |
| Japan | 3 | 2% |
| Spain | 2 | 1% |
| Canada | 2 | 1% |
| Portugal | 2 | 1% |
| India | 2 | 1% |
| Other | 14 | 10% |
| Unknown | 54 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 84 | 58% |
| Members of the public | 57 | 39% |
| Science communicators (journalists, bloggers, editors) | 2 | 1% |
| Practitioners (doctors, other healthcare professionals) | 2 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 347 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 347 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 82 | 24% |
| Researcher | 71 | 20% |
| Student > Master | 28 | 8% |
| Student > Bachelor | 24 | 7% |
| Student > Doctoral Student | 17 | 5% |
| Other | 55 | 16% |
| Unknown | 70 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 110 | 32% |
| Agricultural and Biological Sciences | 83 | 24% |
| Mathematics | 18 | 5% |
| Computer Science | 13 | 4% |
| Medicine and Dentistry | 11 | 3% |
| Other | 35 | 10% |
| Unknown | 77 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 110. 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 28 June 2023.
All research outputs
#390,025
of 25,748,735 outputs
Outputs from Nature Genetics
#770
of 7,615 outputs
Outputs of similar age
#8,396
of 448,574 outputs
Outputs of similar age from Nature Genetics
#16
of 76 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 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,615 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one has done well, scoring higher than 89% 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 448,574 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 98% of its contemporaries.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.