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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Equivalent input produces different output in the UniFrac significance test
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-278 |
| Pubmed ID | |
| Authors |
Jeffrey R Long, Vanessa Pittet, Brett Trost, Qingxiang Yan, David Vickers, Monique Haakensen, Anthony Kusalik |
| Abstract |
UniFrac is a well-known tool for comparing microbial communities and assessing statistically significant differences between communities. In this paper we identify a discrepancy in the UniFrac methodology that causes semantically equivalent inputs to produce different outputs in tests of statistical significance. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 7 | 58% |
| Sweden | 1 | 8% |
| Norway | 1 | 8% |
| Canada | 1 | 8% |
| Unknown | 2 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 3 | 6% |
| United States | 2 | 4% |
| Chile | 1 | 2% |
| Canada | 1 | 2% |
| Sweden | 1 | 2% |
| Unknown | 40 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 21% |
| Student > Ph. D. Student | 9 | 19% |
| Student > Master | 8 | 17% |
| Student > Doctoral Student | 5 | 10% |
| Student > Bachelor | 5 | 10% |
| Other | 7 | 15% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 42% |
| Biochemistry, Genetics and Molecular Biology | 7 | 15% |
| Computer Science | 5 | 10% |
| Environmental Science | 4 | 8% |
| Chemistry | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 4 | 8% |
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 21 April 2015.
All research outputs
#5,435,396
of 25,711,518 outputs
Outputs from BMC Bioinformatics
#1,907
of 7,735 outputs
Outputs of similar age
#49,994
of 243,801 outputs
Outputs of similar age from BMC Bioinformatics
#34
of 116 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,735 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 done well, scoring higher than 75% 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 243,801 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 79% of its contemporaries.
We're also able to compare this research output to 116 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 68% of its contemporaries.