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X Demographics
Mendeley readers
Attention Score in Context
| Title |
OSAT: a tool for sample-to-batch allocations in genomics experiments
|
|---|---|
| Published in |
BMC Genomics, December 2012
|
| DOI | 10.1186/1471-2164-13-689 |
| Pubmed ID | |
| Authors |
Li Yan, Changxing Ma, Dan Wang, Qiang Hu, Maochun Qin, Jeffrey M Conroy, Lara E Sucheston, Christine B Ambrosone, Candace S Johnson, Jianmin Wang, Song Liu |
| Abstract |
Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. |
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 States | 2 | 33% |
| Germany | 1 | 17% |
| Canada | 1 | 17% |
| United Kingdom | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 83% |
| Members of the public | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Sweden | 1 | 2% |
| Unknown | 42 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 23% |
| Student > Ph. D. Student | 7 | 16% |
| Student > Postgraduate | 4 | 9% |
| Professor | 3 | 7% |
| Student > Bachelor | 3 | 7% |
| Other | 12 | 27% |
| Unknown | 5 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 27% |
| Agricultural and Biological Sciences | 11 | 25% |
| Medicine and Dentistry | 4 | 9% |
| Computer Science | 2 | 5% |
| Chemistry | 2 | 5% |
| Other | 6 | 14% |
| Unknown | 7 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 April 2021.
All research outputs
#7,959,659
of 25,373,627 outputs
Outputs from BMC Genomics
#3,479
of 11,244 outputs
Outputs of similar age
#78,345
of 286,419 outputs
Outputs of similar age from BMC Genomics
#65
of 205 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 67% 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 286,419 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 71% of its contemporaries.
We're also able to compare this research output to 205 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 64% of its contemporaries.