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Attention Score in Context
| Title |
Genome-wide association analyses of the 15th QTL-MAS workshop data using mixed model based single locus regression analysis
|
|---|---|
| Published in |
BMC Proceedings, May 2012
|
| DOI | 10.1186/1753-6561-6-s2-s5 |
| Pubmed ID | |
| Authors |
Wei-Xuan Fu, Chong-Long Wang, Xiang-Dong Ding, Zhe Zhang, Pei-Pei Ma, Zi-Qing Weng, Jian-Feng Liu, Qin Zhang |
| Abstract |
The mixed model based single locus regression analysis (MMRA) method was used to analyse the common simulated dataset of the 15th QTL-MAS workshop to detect potential significant association between single nucleotide polymorphisms (SNPs) and the simulated trait. A Wald chi-squared statistic with df =1 was employed as test statistic and the permutation test was performed. For adjusting multiple testing, phenotypic observations were permutated 10,000 times against the genotype and pedigree data to obtain the threshold for declaring genome-wide significant SNPs. Linkage disequilibrium (LD) in term of D' between significant SNPs was quantified and LD blocks were defined to indicate quantitative trait loci (QTL) regions. |
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 % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Benin | 1 | 7% |
| Brazil | 1 | 7% |
| Unknown | 13 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 47% |
| Researcher | 3 | 20% |
| Student > Doctoral Student | 2 | 13% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 93% |
| Unknown | 1 | 7% |
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 31 May 2012.
All research outputs
#18,308,895
of 22,668,244 outputs
Outputs from BMC Proceedings
#265
of 374 outputs
Outputs of similar age
#125,954
of 163,633 outputs
Outputs of similar age from BMC Proceedings
#10
of 16 outputs
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