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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CollapsABEL: an R library for detecting compound heterozygote alleles in genome-wide association studies
|
|---|---|
| Published in |
BMC Bioinformatics, April 2016
|
| DOI | 10.1186/s12859-016-1006-9 |
| Pubmed ID | |
| Authors |
Kaiyin Zhong, Lennart C. Karssen, Manfred Kayser, Fan Liu |
| Abstract |
Compound Heterozygosity (CH) in classical genetics is the presence of two different recessive mutations at a particular gene locus. A relaxed form of CH alleles may account for an essential proportion of the missing heritability, i.e. heritability of phenotypes so far not accounted for by single genetic variants. Methods to detect CH-like effects in genome-wide association studies (GWAS) may facilitate explaining the missing heritability, but to our knowledge no viable software tools for this purpose are currently available. In this work we present the Generalized Compound Double Heterozygosity (GCDH) test and its implementation in the R package CollapsABEL. Time-consuming procedures are optimized for computational efficiency using Java or C++. Intermediate results are stored either in an SQL database or in a so-called big.matrix file to achieve reasonable memory footprint. Our large scale simulation studies show that GCDH is capable of discovering genetic associations due to CH-like interactions with much higher power than a conventional single-SNP approach under various settings, whether the causal genetic variations are available or not. CollapsABEL provides a user-friendly pipeline for genotype collapsing, statistical testing, power estimation, type I error control and graphics generation in the R language. CollapsABEL provides a computationally efficient solution for screening general forms of CH alleles in densely imputed microarray or whole genome sequencing datasets. The GCDH test provides an improved power over single-SNP based methods in detecting the prevalence of CH in human complex phenotypes, offering an opportunity for tackling the missing heritability problem. Binary and source packages of CollapsABEL are available on CRAN ( https://cran.r-project.org/web/packages/CollapsABEL ) and the website of the GenABEL project ( http://www.genabel.org/packages ). |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 37 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 28% |
| Researcher | 9 | 23% |
| Other | 3 | 8% |
| Student > Master | 3 | 8% |
| Student > Bachelor | 2 | 5% |
| Other | 1 | 3% |
| Unknown | 10 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 23% |
| Biochemistry, Genetics and Molecular Biology | 8 | 21% |
| Computer Science | 5 | 13% |
| Mathematics | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 14 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 22 April 2016.
All research outputs
#13,230,163
of 22,860,626 outputs
Outputs from BMC Bioinformatics
#4,008
of 7,294 outputs
Outputs of similar age
#142,889
of 300,802 outputs
Outputs of similar age from BMC Bioinformatics
#63
of 116 outputs
Altmetric has tracked 22,860,626 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,294 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 300,802 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 51% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.