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Mendeley readers
Attention Score in Context
| Title |
Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias
|
|---|---|
| Published in |
BMC Genomics, January 2012
|
| DOI | 10.1186/1471-2164-13-34 |
| Pubmed ID | |
| Authors |
John P Didion, Hyuna Yang, Keith Sheppard, Chen-Ping Fu, Leonard McMillan, Fernando Pardo-Manuel de Villena, Gary A Churchill |
| Abstract |
High-density genotyping arrays that measure hybridization of genomic DNA fragments to allele-specific oligonucleotide probes are widely used to genotype single nucleotide polymorphisms (SNPs) in genetic studies, including human genome-wide association studies. Hybridization intensities are converted to genotype calls by clustering algorithms that assign each sample to a genotype class at each SNP. Data for SNP probes that do not conform to the expected pattern of clustering are often discarded, contributing to ascertainment bias and resulting in lost information - as much as 50% in a recent genome-wide association study in dogs. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Australia | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Australia | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 62 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 24% |
| Researcher | 15 | 22% |
| Student > Master | 10 | 15% |
| Student > Bachelor | 8 | 12% |
| Professor > Associate Professor | 4 | 6% |
| Other | 11 | 16% |
| Unknown | 3 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 37 | 55% |
| Computer Science | 7 | 10% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Medicine and Dentistry | 3 | 4% |
| Immunology and Microbiology | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 7 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 26 July 2021.
All research outputs
#3,759,146
of 22,661,413 outputs
Outputs from BMC Genomics
#1,550
of 10,612 outputs
Outputs of similar age
#32,613
of 245,768 outputs
Outputs of similar age from BMC Genomics
#43
of 279 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,612 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 85% 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 245,768 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 279 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.