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Mendeley readers
Attention Score in Context
| Title |
Fast genome-wide pedigree quantitative trait loci analysis using MENDEL
|
|---|---|
| Published in |
BMC Proceedings, June 2014
|
| DOI | 10.1186/1753-6561-8-s1-s93 |
| Pubmed ID | |
| Authors |
Hua Zhou, Jin Zhou, Eric M Sobel, Kenneth Lange |
| Abstract |
The linkage era left a rich legacy of pedigree samples that can be used for modern genome-wide association sequencing (GWAS) or next-generation sequencing (NGS) studies. Family designs are naturally equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Unfortunately, pedigree likelihoods are notoriously hard to compute, and current software for association mapping in pedigrees is prohibitively slow in processing dense marker maps. In a recent release of the comprehensive genetic analysis software MENDEL, we implemented an ultra-fast score test for association mapping with pedigree-based GWAS or NGS study data. Our implementation (a) works for random sample data, pedigree data, or a mix of both;(b) allows for covariate adjustment, including correction for population stratification;(c) accommodates both univariate and multivariate quantitative traits; and (d) allows missing values in multivariate traits. In this paper, we assess the capabilities of MENDEL on the Genetic Analysis Workshop 18 sequencing data. For instance, when jointly testing the 4 longitudinally measured diastolic blood pressure traits, it takes MENDEL less than 51 minutes on a standard laptop computer to read, quality check, and analyze a data set with 959 individuals and 8.3 million single-nucleotide polymorphisms (SNPs). Our analysis reveals association of one SNP in the q32.2 region of chromosome 1. MENDEL is freely available on http://www.genetics.ucla.edu/software. |
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 % |
|---|---|---|
| Scientists | 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 % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 54% |
| Lecturer | 2 | 15% |
| Professor | 1 | 8% |
| Student > Master | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 38% |
| Agricultural and Biological Sciences | 3 | 23% |
| Mathematics | 1 | 8% |
| Environmental Science | 1 | 8% |
| Business, Management and Accounting | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |
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 19 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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