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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Meta-Analysis in Gene Expression Studies
|
|---|---|
| Chapter number | 8 |
| Book title |
Statistical Genomics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3578-9_8 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3576-5, 978-1-4939-3578-9
|
| Authors |
Levi Waldron, Markus Riester, Waldron, Levi, Riester, Markus |
| Editors |
Ewy Mathé, Sean Davis |
| Abstract |
This chapter introduces methods to synthesize experimental results from independent high-throughput genomic experiments, with a focus on adaptation of traditional methods from systematic review of clinical trials and epidemiological studies. First, it reviews methods for identifying, acquiring, and preparing individual patient data for meta-analysis. It then reviews methodology for synthesizing results across studies and assessing heterogeneity, first through outlining of methods and then through a step-by-step case study in identifying genes associated with survival in high-grade serous ovarian cancer. |
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% |
| United Kingdom | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 50% |
| Members of the public | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 40 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 29% |
| Researcher | 7 | 17% |
| Student > Master | 4 | 10% |
| Student > Doctoral Student | 3 | 7% |
| Professor > Associate Professor | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 8 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 32% |
| Agricultural and Biological Sciences | 5 | 12% |
| Medicine and Dentistry | 5 | 12% |
| Neuroscience | 3 | 7% |
| Computer Science | 2 | 5% |
| Other | 1 | 2% |
| Unknown | 12 | 29% |
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 16 August 2016.
All research outputs
#13,229,909
of 23,314,015 outputs
Outputs from Methods in molecular biology
#3,380
of 13,320 outputs
Outputs of similar age
#182,349
of 396,039 outputs
Outputs of similar age from Methods in molecular biology
#315
of 1,474 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,320 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 73% 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 396,039 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 53% of its contemporaries.
We're also able to compare this research output to 1,474 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.