R: Genomic control for various model of inheritance using VIF
VIFGC
R Documentation
Genomic control for various model of inheritance using VIF
Description
This function estimates corrected statistic using genomic
control for different models (recessive, dominant,
additive etc.), using VIF. VIF coefficients are estimated
by optimizing different error functions: regress, median
and ks.test.
Usage
VIFGC(data, p, x, method = "regress", n,
index.filter = NULL, proportion = 1, clust = 0,
vart0 = 0, tmp = 0, CA = FALSE, p.table = 0,
plot = TRUE, lmax = NULL, color = "red", F = NULL,
K = NULL, type_of_plot = "plot", ladd = NULL)
Arguments
data
Input vector of Chi square statistic
method
Function of error to be optimized. Can be
"regress", "median" or "ks.test"
p
Input vector of allele frequencies
x
Model of inheritance (0 for recessive,0.5 for
additive, 1 for dominant, also it could be arbitrary)
index.filter
Indexes for variables that will be
use for analysis in data vector
n
The size of the sample
proportion
The proportion of lowest P (Chi2) to be
used when estimating the inflation factor Lambda for
"regress" method only
plot
If TRUE, plot of lambda will be produced
type_of_plot
For developers only
lmax
The threshold for lambda for plotting
(optional)
color
The color of the plot
F
The estimation of F (optional)
K
The estimation of K (optional)
ladd
The estimation of lambda for additive model
(optional)
clust
For developers only
vart0
For developers only
tmp
For developers only
CA
For developers only
p.table
For developers only
Value
A list with elements
Zx
output vector corrected
Chi square statistic
vv
output vector of VIF
exeps
output vector of exepsons (NA)
calrate
output vector of calrate
F
F
K
K
Author(s)
Yakov Tsepilov
Examples
require(GenABEL.data)
data(ge03d2)
# truncate the data to make the example faster
ge03d2 <- ge03d2[seq(from=1,to=nids(ge03d2),by=2),seq(from=1,to=nsnps(ge03d2),by=3)]
qts <- mlreg(dm2~sex,data=ge03d2,gtmode = "dominant")
chi2.1df <- results(qts)$chi2.1df
s <- summary(ge03d2)
freq <- s$Q.2
result <- VIFGC(p=freq,x=1,method = "median",CA=FALSE,data=chi2.1df,n=nids(ge03d2))
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(GenABEL)
Loading required package: MASS
Loading required package: GenABEL.data
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GenABEL/VIFGC.Rd_%03d_medium.png", width=480, height=480)
> ### Name: VIFGC
> ### Title: Genomic control for various model of inheritance using VIF
> ### Aliases: VIFGC
> ### Keywords: htest
>
> ### ** Examples
>
> require(GenABEL.data)
> data(ge03d2)
> # truncate the data to make the example faster
> ge03d2 <- ge03d2[seq(from=1,to=nids(ge03d2),by=2),seq(from=1,to=nsnps(ge03d2),by=3)]
> qts <- mlreg(dm2~sex,data=ge03d2,gtmode = "dominant")
> chi2.1df <- results(qts)$chi2.1df
> s <- summary(ge03d2)
> freq <- s$Q.2
> result <- VIFGC(p=freq,x=1,method = "median",CA=FALSE,data=chi2.1df,n=nids(ge03d2))
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.