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Mendeley readers
Attention Score in Context
| Title |
Current software for genotype imputation
|
|---|---|
| Published in |
Human Genomics, July 2009
|
| DOI | 10.1186/1479-7364-3-4-371 |
| Pubmed ID | |
| Authors |
David Ellinghaus, Stefan Schreiber, Andre Franke, Michael Nothnagel |
| Abstract |
Genotype imputation for single nucleotide polymorphisms (SNPs) has been shown to be a powerful means to include genetic markers in exploratory genetic association studies without having to genotype them, and is becoming a standard procedure. A number of different software programs are available. In our experience, user-friendliness is often the deciding factor in the choice of software to solve a particular task. We therefore evaluated the usability of three publicly available imputation programs: BEAGLE, IMPUTE and MACH. We found all three programs to perform well with HapMap reference data, with little effort needed for data preparation and subsequent association analysis. Each of them has different strengths and weaknesses, however, and none is optimal for all situations. |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 5 | 5% |
| United States | 2 | 2% |
| Netherlands | 1 | 1% |
| Brazil | 1 | 1% |
| New Zealand | 1 | 1% |
| Finland | 1 | 1% |
| Denmark | 1 | 1% |
| Belgium | 1 | 1% |
| Unknown | 80 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 34% |
| Student > Ph. D. Student | 17 | 18% |
| Student > Master | 10 | 11% |
| Student > Doctoral Student | 8 | 9% |
| Student > Postgraduate | 7 | 8% |
| Other | 14 | 15% |
| Unknown | 5 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 47 | 51% |
| Biochemistry, Genetics and Molecular Biology | 17 | 18% |
| Mathematics | 6 | 6% |
| Medicine and Dentistry | 5 | 5% |
| Computer Science | 4 | 4% |
| Other | 5 | 5% |
| Unknown | 9 | 10% |
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 15 June 2011.
All research outputs
#14,602,949
of 25,377,790 outputs
Outputs from Human Genomics
#279
of 564 outputs
Outputs of similar age
#100,587
of 122,287 outputs
Outputs of similar age from Human Genomics
#3
of 3 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 48th percentile – i.e., 48% 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 122,287 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.