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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Fast accurate missing SNP genotype local imputation
|
|---|---|
| Published in |
BMC Research Notes, August 2012
|
| DOI | 10.1186/1756-0500-5-404 |
| Pubmed ID | |
| Authors |
Yining Wang, Zhipeng Cai, Paul Stothard, Steve Moore, Randy Goebel, Lusheng Wang, Guohui Lin |
| Abstract |
Single nucleotide polymorphism (SNP) genotyping assays normally give rise to certain percents of no-calls; the problem becomes severe when the target organisms, such as cattle, do not have a high resolution genomic sequence. Missing SNP genotypes, when related to target traits, would confound downstream data analyses such as genome-wide association studies (GWAS). Existing methods for recovering the missing values are successful to some extent - either accurate but not fast enough or fast but not accurate enough. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 48 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 24% |
| Student > Ph. D. Student | 8 | 16% |
| Student > Master | 7 | 14% |
| Student > Bachelor | 5 | 10% |
| Student > Doctoral Student | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 7 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 44% |
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Computer Science | 5 | 10% |
| Medicine and Dentistry | 2 | 4% |
| Mathematics | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 9 | 18% |
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 14 August 2012.
All research outputs
#18,312,024
of 22,673,450 outputs
Outputs from BMC Research Notes
#3,006
of 4,250 outputs
Outputs of similar age
#126,183
of 164,736 outputs
Outputs of similar age from BMC Research Notes
#76
of 102 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,250 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 16th percentile – i.e., 16% 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 164,736 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.