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Last data update: 2014.03.03

R: MAX CATT test in case-control genetic association analysis

Exact Max CATT Test

R Documentation

MAX CATT test in case-control genetic association analysis

Description

Perform exact MAX3 test, MAX2 test and Cochran-Armitage trend test for one-locus genetic association analysis. MAX3 is the maximum of the Cochran-Armitage trend test statistic for dominant, recessive and additive models, and MAX2 is the maximum of dominant and recessive models.

It also provides approximated p-value of a MAX test with the normal approximation method.

Usage

maxact.test(data, max3 = TRUE, exact=TRUE, alternative = "two.sided")
catt.test(data, theta, exact=TRUE, alternative = "two.sided")

Arguments

`data`	2x3 contingency table of data values, with rows representing case/control, and columns representing the three genotypes
`max3`	a logical indicating whether MAX3 or MAX2 test statistic should be used
`theta`	parameter of the Cochran-Armitage trend test
`exact`	a logical indicating whether an exact p-value should be computed
`alternative`	a character string describing the alternative hypothesis, which must be one of '"two.sided"', '"greater"' or '"less"'

Value

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

`data.name`	a character string giving the names of the data.
`p.value`	the p-value of the test.
`method`	a character string describing the method used.
`statistic`	the value of the test statistic.
`alternative`	a character string describing the alternative hypothesis.

Note

The normal approximation method(exact=FALSE) is provided for comparison purpose, and is not recommended for data analysis. The exact method is faster than the normal approximation method in most of cases, and it is fast enough for most of applications.

Author(s)

Jianan Tian jiant17@gmail.com, Chenliang Xu lucky.random@gmail.com

References

Tian, J., Xu, C., Zhan, H., Yang, Y. (2009) "Exact MAX tests in case-control association analysis (Manuscript)."

Examples

data.sladek <- matrix(c(129, 326, 229, 198, 325, 143), 2, 3, byrow=TRUE)

## MAX3 test (exact p-value)
maxact.test(data.sladek) 

## MAX2 test (exact p-value):
maxact.test(data.sladek, max3=FALSE, exact=TRUE)


## MAX test (p-value calculated from the normal approximation method), it
## is not recommends, see NOTE for more information
 maxact.test(data.sladek, max3=TRUE, exact=FALSE)
 maxact.test(data.sladek, max3=FALSE, exact=FALSE)

## Cochran-Armitage trend test, assuming we know the model 
 catt.test(data.sladek, theta=0)    #recessive model
 catt.test(data.sladek, theta=0.5)  #additive model
 catt.test(data.sladek, theta=1)    #dominant model

#the  alternative hypothesis is less
 catt.test(data.sladek, theta=0, alternative="less")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MaXact)
Loading required package: mnormt
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MaXact/maxact.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Exact Max CATT Test
> ### Title: MAX CATT test in case-control genetic association analysis
> ### Aliases: MaXact maxact.test catt.test
> ### Keywords: htest
> 
> ### ** Examples
> 
> data.sladek <- matrix(c(129, 326, 229, 198, 325, 143), 2, 3, byrow=TRUE)
> 
> ## MAX3 test (exact p-value)
> maxact.test(data.sladek) 

	Exact MAX3 test

data:  data.sladek (2x3 contingency table)
max3 = 5.8467, p-value = 1.288e-08
alternative hypothesis: two.sided

> 
> ## MAX2 test (exact p-value):
> maxact.test(data.sladek, max3=FALSE, exact=TRUE)

	Exact MAX2 test

data:  data.sladek (2x3 contingency table)
max2 = 4.937, p-value = 1.436e-06
alternative hypothesis: two.sided

> 
> 
> ## MAX test (p-value calculated from the normal approximation method), it
> ## is not recommends, see NOTE for more information
>  maxact.test(data.sladek, max3=TRUE, exact=FALSE)

	MAX3 test (normal approximation)

data:  data.sladek (2x3 contingency table)
max3 = 5.8467, p-value = 8.915e-09
alternative hypothesis: two.sided

>  maxact.test(data.sladek, max3=FALSE, exact=FALSE)

	MAX2 test (normal approximation)

data:  data.sladek (2x3 contingency table)
max2 = 4.937, p-value = 1.586e-06
alternative hypothesis: two.sided

> 
> ## Cochran-Armitage trend test, assuming we know the model 
>  catt.test(data.sladek, theta=0)    #recessive model

	Exact Cochran-Armitage trend test with theta 0

data:  data.sladek (2x3 contingency table)
CATT(0) = -4.937, p-value = 7.758e-07
alternative hypothesis: two.sided

>  catt.test(data.sladek, theta=0.5)  #additive model

	Exact Cochran-Armitage trend test with theta 0.5

data:  data.sladek (2x3 contingency table)
CATT(0.5) = -5.8467, p-value = 4.879e-09
alternative hypothesis: two.sided

>  catt.test(data.sladek, theta=1)    #dominant model

	Exact Cochran-Armitage trend test with theta 1

data:  data.sladek (2x3 contingency table)
CATT(1) = -4.6607, p-value = 3.351e-06
alternative hypothesis: two.sided

> 
> #the  alternative hypothesis is less
>  catt.test(data.sladek, theta=0, alternative="less") 

	Exact Cochran-Armitage trend test with theta 0

data:  data.sladek (2x3 contingency table)
CATT(0) = -4.937, p-value = 4.967e-07
alternative hypothesis: less

> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>