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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RNA-Seq optimization with eQTL gold standards
|
|---|---|
| Published in |
BMC Genomics, December 2013
|
| DOI | 10.1186/1471-2164-14-892 |
| Pubmed ID | |
| Authors |
Shannon E Ellis, Simone Gupta, Foram N Ashar, Joel S Bader, Andrew B West, Dan E Arking |
| Abstract |
RNA-Sequencing (RNA-Seq) experiments have been optimized for library preparation, mapping, and gene expression estimation. These methods, however, have revealed weaknesses in the next stages of analysis of differential expression, with results sensitive to systematic sample stratification or, in more extreme cases, to outliers. Further, a method to assess normalization and adjustment measures imposed on the data is lacking. |
X Demographics
The data shown below were collected from the profiles of 18 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 | 5 | 28% |
| Sweden | 1 | 6% |
| Brazil | 1 | 6% |
| France | 1 | 6% |
| United Kingdom | 1 | 6% |
| Unknown | 9 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 50% |
| Members of the public | 6 | 33% |
| Science communicators (journalists, bloggers, editors) | 2 | 11% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 6% |
| Sweden | 1 | <1% |
| Germany | 1 | <1% |
| China | 1 | <1% |
| Argentina | 1 | <1% |
| Unknown | 107 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 41 | 35% |
| Student > Ph. D. Student | 28 | 24% |
| Student > Master | 9 | 8% |
| Professor > Associate Professor | 7 | 6% |
| Other | 6 | 5% |
| Other | 16 | 14% |
| Unknown | 11 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 61 | 52% |
| Biochemistry, Genetics and Molecular Biology | 27 | 23% |
| Computer Science | 7 | 6% |
| Neuroscience | 4 | 3% |
| Medicine and Dentistry | 3 | 3% |
| Other | 2 | 2% |
| Unknown | 14 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 09 November 2022.
All research outputs
#1,791,277
of 24,689,476 outputs
Outputs from BMC Genomics
#390
of 11,045 outputs
Outputs of similar age
#18,828
of 297,607 outputs
Outputs of similar age from BMC Genomics
#25
of 452 outputs
Altmetric has tracked 24,689,476 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,045 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 96% 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 297,607 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 93% of its contemporaries.
We're also able to compare this research output to 452 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.