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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Meta-analysis based on weighted ordered P-values for genomic data with heterogeneity
|
|---|---|
| Published in |
BMC Bioinformatics, June 2014
|
| DOI | 10.1186/1471-2105-15-226 |
| Pubmed ID | |
| Authors |
Yihan Li, Debashis Ghosh |
| Abstract |
Meta-analysis has become increasingly popular in recent years, especially in genomic data analysis, due to the fast growth of available data and studies that target the same questions. Many methods have been developed, including classical ones such as Fisher's combined probability test and Stouffer's Z-test. However, not all meta-analyses have the same goal in mind. Some aim at combining information to find signals in at least one of the studies, while others hope to find more consistent signals across the studies. While many classical meta-analysis methods are developed with the former goal in mind, the latter goal has much more practicality for genomic data analysis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Netherlands | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 54 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 28% |
| Researcher | 8 | 14% |
| Student > Master | 7 | 12% |
| Professor | 5 | 9% |
| Student > Doctoral Student | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 31% |
| Biochemistry, Genetics and Molecular Biology | 7 | 12% |
| Computer Science | 7 | 12% |
| Mathematics | 4 | 7% |
| Medicine and Dentistry | 3 | 5% |
| Other | 9 | 16% |
| Unknown | 10 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 2014.
All research outputs
#20,231,820
of 22,757,541 outputs
Outputs from BMC Bioinformatics
#6,844
of 7,272 outputs
Outputs of similar age
#192,154
of 227,594 outputs
Outputs of similar age from BMC Bioinformatics
#142
of 153 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,272 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 227,594 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 153 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.