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Mendeley readers
Attention Score in Context
| Title |
Evaluating the performance of Affymetrix SNP Array 6.0 platform with 400 Japanese individuals
|
|---|---|
| Published in |
BMC Genomics, September 2008
|
| DOI | 10.1186/1471-2164-9-431 |
| Pubmed ID | |
| Authors |
Nao Nishida, Asako Koike, Atsushi Tajima, Yuko Ogasawara, Yoshimi Ishibashi, Yasuka Uehara, Ituro Inoue, Katsushi Tokunaga |
| Abstract |
With improvements in genotyping technologies, genome-wide association studies with hundreds of thousands of SNPs allow the identification of candidate genetic loci for multifactorial diseases in different populations. However, genotyping errors caused by genotyping platforms or genotype calling algorithms may lead to inflation of false associations between markers and phenotypes. In addition, the number of SNPs available for genome-wide association studies in the Japanese population has been investigated using only 45 samples in the HapMap project, which could lead to an inaccurate estimation of the number of SNPs with low minor allele frequencies. We genotyped 400 Japanese samples in order to estimate the number of SNPs available for genome-wide association studies in the Japanese population and to examine the performance of the current SNP Array 6.0 platform and the genotype calling algorithm "Birdseed". |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 3 | 5% |
| Hong Kong | 1 | 2% |
| United States | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 60 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 33% |
| Student > Master | 9 | 14% |
| Student > Ph. D. Student | 8 | 12% |
| Student > Postgraduate | 5 | 8% |
| Student > Bachelor | 4 | 6% |
| Other | 11 | 17% |
| Unknown | 7 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 38 | 58% |
| Biochemistry, Genetics and Molecular Biology | 9 | 14% |
| Medicine and Dentistry | 5 | 8% |
| Computer Science | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 10 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 24 July 2023.
All research outputs
#5,446,210
of 25,371,288 outputs
Outputs from BMC Genomics
#2,155
of 11,244 outputs
Outputs of similar age
#19,908
of 99,378 outputs
Outputs of similar age from BMC Genomics
#8
of 48 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 79% 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 99,378 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 70% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.