ArticleBMC bioinformatics2016
CollapsABEL: an R library for detecting compound heterozygote alleles in genome-wide association studies.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Decreased Immunoglobulin G Core Fucosylation, A Player in Antibody-dependent Cell-mediated Cytotoxicity, is Associated with Autoimmune Thyroid Diseases.Molecular & cellular proteomics : MCP · 2020Article
- In trans variant calling reveals enrichment for compound heterozygous variants in genes involved in neuronal development and growth.Genetics research · 2019Article
- DNA sequence-level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders.Molecular psychiatry · 2018Article
- Genome-wide compound heterozygote analysis highlights alleles associated with adult height in Europeans.Human genetics · 2017Article
- DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.Forensic science international. Genetics · 2017Article
- The GenABEL Project for statistical genomics.F1000Research · 2016Article
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4 authors.
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Abstract
backgroundCompound 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.
resultsIn 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.
conclusionsCollapsABEL 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 ).
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