Description Arguments Value Author(s)
Compound Heterozygosity (CH) in classical genetics is the presen-ce of two different recessive mutations at a particular gene locus, one on each chromosome . The presence of CH has been found for nearly all autosomal recessive disorders as well as other phenotypes such as red hair color. A relaxed form of CH, i.e., in which the genetic variants are not necessarily coding, rare, and deleterious, is likely involved in a wide range of human polygenic traits and referred to as generalized CH (GCH). Howev-er, individually analyzing a large number of DNA sequence vari-ants, as being the routine in genome-wide association studies (GWAS), has limited power to detect genetic associations caused by GCH, which may be partially responsible for the currently still "missing heritability". Existing tools specifically designed for detecting GCH alleles are scarce, in particular for the analysis of densely imputed Single Nucleotide Polymorphism (SNP) array data or whole genome se-quencing data. Previously, we developed a collapsed double heter-ozygosity (CDH) test for detecting the association between CH genotypes and binary traits by applying a chi-squared statistic to pseudo-genotypes collapsed from a pair of SNPs, which was implemented as a function in the GenABEL R package . Here, we implement a generalized CDH (GCDH) method to overcome previous limitations and allow (1) fast analysis of densely imputed SNP data or whole genome se-quencing data; (2) flexible analysis of binary and quantitative traits with covariates; (3) empirical power estimation and type-I error control; and (4) easy interface with graphical utilities
phe_file |
character. Phenotype file. |
FALSE when the file is invalid, or a data.frame when it is.
Kaiyin Zhong, Fan Liu
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