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Attention Score in Context
| Title |
Combining information from linkage and association mapping for next-generation sequencing longitudinal family data
|
|---|---|
| Published in |
BMC Proceedings, June 2014
|
| DOI | 10.1186/1753-6561-8-s1-s34 |
| Pubmed ID | |
| Authors |
Brunilda Balliu, Hae-Won Uh, Roula Tsonaka, Stefan Boehringer, Quinta Helmer, Jeanine J Houwing-Duistermaat |
| Abstract |
In this analysis, we investigate the contributions that linkage-based methods, such as identical-by-descent mapping, can make to association mapping to identify rare variants in next-generation sequencing data. First, we identify regions in which cases share more segments identical-by-descent around a putative causal variant than do controls. Second, we use a two-stage mixed-effect model approach to summarize the single-nucleotide polymorphism data within each region and include them as covariates in the model for the phenotype. We assess the impact of linkage disequilibrium in determining identical-by-descent states between individuals by using markers with and without linkage disequilibrium for the first part and the impact of imputation in testing for association by using imputed genome-wide association studies or raw sequence markers for the second part. We apply the method to next-generation sequencing longitudinal family data from Genetic Association Workshop 18 and identify a significant region at chromosome 3: 40249244-41025167 (p-value = 2.3 × 10(-3)). |
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 % |
|---|---|---|
| United States | 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 8% |
| Unknown | 12 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 31% |
| Student > Ph. D. Student | 3 | 23% |
| Professor > Associate Professor | 2 | 15% |
| Other | 1 | 8% |
| Student > Master | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 31% |
| Biochemistry, Genetics and Molecular Biology | 3 | 23% |
| Mathematics | 2 | 15% |
| Computer Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 2 | 15% |
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 24 December 2014.
All research outputs
#18,387,239
of 22,775,504 outputs
Outputs from BMC Proceedings
#265
of 374 outputs
Outputs of similar age
#163,822
of 228,203 outputs
Outputs of similar age from BMC Proceedings
#9
of 21 outputs
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So far Altmetric has tracked 374 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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