AssocTests (version 1.0-1)

dr: Distance regression

Description

Conduct the distance regression with or without the adjustment of the covariates to detect the association between a distance matrix and some independent variants of interest.

Usage

dr(
  simi.mat,
  null.space,
  x.mat,
  permute = TRUE,
  n.MonteCarlo = 1000,
  seed = NULL
)

Arguments

simi.mat

a similarity matrix among the subjects.

null.space

a numeric vector to show the column numbers of the null space in x.mat.

x.mat

the covariate matrix which combines the null space and the matrix of interest.

permute

logical. If TRUE, the Monte Carlo sampling is used without replacement; otherwise, with replacement. The default is TRUE.

n.MonteCarlo

the number of times for the Monte Carlo procedure. The default is 1000.

seed

if it is not NULL, set the random number generator state for random number generation. The default is NULL.

Value

A list with class "htest" containing the following components:

statistic
			the observed value of the test statistic.
p.value
			the p-value for the test.
alternative
			a character string describing the alternative hypothesis.
method
			a character string indicating the type of test performed.
data.name

Details

The pseudo F statistic based on the distance regression with or without the adjustment of the covariates detects the association between a distance matrix and some independent variants of interest. A distance matrix can be transformed into a similarity matrix easily.

References

Lin Wang, Wei Zhang, and Qizhai Li. AssocTests: An R Package for Genetic Association Studies. Journal of Statistical Software. 2020; 94(5): 1-26.

Q Li, S Wacholder, DJ Hunter, RN Hoover, S Chanock, G Thomas, and K Yu. Genetic Background Comparison Using Distance-Based Regression, with Applications in Population Stratification Evaluation and Adjustment. Genetic Epidemiology. 2009; 33(5): 432-441.

J Wessel and NJ Schork. Generalized Genomic Distance-Based Regression Methodology for Multilocus Association Analysis. American Journal of Human Genetics. 2006; 79(5): 792-806.

MA Zapala and NJ Schork. Multivariate Regression Analysis of Distance Matrices for Testing Associations Between Gene Expression Patterns and Related Variables. Proceedings of the National Academy of Sciences of the United States of America. 2006; 103(51): 19430-19435.

Examples

# NOT RUN {
data(drS.eg)
null.space <- 1
x.mat <- matrix(c(rep(1, 600), rep(0, 200)), ncol=2)
dr(drS.eg, null.space, x.mat, permute = TRUE, n.MonteCarlo = 50, seed = NULL)
# }