rankTransPheno: Rank-Based Inverse Normal Transformation

In FRGEpistasis: Epistasis Analysis for Quantitative Traits by Functional Regression Model

Description

Rank-Based Inverse Normal Transformation of Phenotype

Usage

rankTransPheno(pheno, para_c)

Arguments

pheno	Vector of phenotype which is the quantitative trait.
para_c	Adjust parameter, commonly as 0,1/3,3/8 or 1/2.

Details

Some variables are not normally distributed. And using statistical tests on this data can give misleading results because they do not meet the statistical assumptions. This function implements Rank-Based Inverse Normal Transformation to make phenotype normally distributed.

Value

Return vector of rank-based inverse normal transformed phenotype.

Author(s)

Futao Zhang

References

T. Mark Beasley, Stephen Erickson and David B. Allison. Rank-Based Inverse Normal Transformations are Increasingly Used, But are They Merited? Behav Genet. 2009 Sep.;39(5):580-595.

Examples

c=0.5
smp_num=100
pheno<-sample(c(0:500),smp_num,replace=TRUE)
rankTransPheno(pheno,c)

FRGEpistasis documentation built on Nov. 8, 2020, 5:51 p.m.