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X Demographics
Mendeley readers
Attention Score in Context
| Title |
readat: An R package for reading and working with SomaLogic ADAT files
|
|---|---|
| Published in |
BMC Bioinformatics, May 2016
|
| DOI | 10.1186/s12859-016-1007-8 |
| Pubmed ID | |
| Authors |
Richard J. Cotton, Johannes Graumann |
| Abstract |
SomaLogic's SOMAscan™ assay platform allows the analysis of the relative abundance of over 1300 proteins directly from biological matrices such as blood plasma and serum. The data resulting from the assay is provided in a proprietary text-based format not easily imported into R. readat is an R package for working with the SomaLogic ADAT file format. It provides functionality for importing, transforming and annotating data from these files. The package is free, open source, and available on Bioconductor and Bitbucket. readat integrates into both Bioconductor and traditional R workflows, rendering it easy to make use of ADAT files. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 1 | 17% |
| Belgium | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Cuba | 1 | 3% |
| Unknown | 32 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 6 | 18% |
| Researcher | 6 | 18% |
| Student > Ph. D. Student | 5 | 15% |
| Other | 4 | 12% |
| Student > Master | 4 | 12% |
| Other | 2 | 6% |
| Unknown | 6 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 15% |
| Computer Science | 5 | 15% |
| Medicine and Dentistry | 5 | 15% |
| Agricultural and Biological Sciences | 3 | 9% |
| Neuroscience | 2 | 6% |
| Other | 4 | 12% |
| Unknown | 9 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 08 August 2017.
All research outputs
#7,753,480
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#3,084
of 7,418 outputs
Outputs of similar age
#108,631
of 300,671 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 102 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 300,671 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 55% of its contemporaries.
We're also able to compare this research output to 102 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 54% of its contemporaries.