R: Calculation of classical multiple testing statistics and...
raw.pvalues
R Documentation
Calculation of classical multiple testing statistics and p-values
Description
Calculates for each gene expression, the Fisher test statistics and the corresponding p-value for H0: the gene expression does not depend on the experimental condition in a model with possible covariates.
Usage
raw.pvalues(data, x = 1, test = x[1])
Arguments
data
'FAMTdata' object, see as.FAMTdata
x
Column number(s) corresponding to the experimental condition and the optional covariates (1 by default) in the 'covariates' data frame.
test
Column number corresponding to the experimental condition (x[1] by default) of interest in the multiple testing procedure.
Value
pval
Vector containing the p-values
test
Vector containing the F statistics
resdf
Residual degrees of freedom
Author(s)
David Causeur
See Also
as.FAMTdata
Examples
data(expression)
data(covariates)
data(annotations)
# Create the 'FAMTdata'
############################################
chicken = as.FAMTdata(expression,covariates,annotations,idcovar=2)
# 'FAMTdata' summary
summaryFAMT(chicken)
# Calculation of classical p-values
############################################
# test on the 6th covariate:
rawpval = raw.pvalues(chicken,x=6)
hist(rawpval$pval)
# with a supplementary covariate (third column of the covariates data frame)
## Not run: rawpval = raw.pvalues(chicken,x=c(3,6),test=6)
## Not run: hist(rawpval$pval)
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(FAMT)
Loading required package: mnormt
Loading required package: impute
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FAMT/raw.pvalues.Rd_%03d_medium.png", width=480, height=480)
> ### Name: raw.pvalues
> ### Title: Calculation of classical multiple testing statistics and
> ### p-values
> ### Aliases: raw.pvalues
>
> ### ** Examples
>
> data(expression)
> data(covariates)
> data(annotations)
>
> # Create the 'FAMTdata'
> ############################################
> chicken = as.FAMTdata(expression,covariates,annotations,idcovar=2)
$`Rows with missing values`
integer(0)
$`Columns with missing values`
integer(0)
> # 'FAMTdata' summary
> summaryFAMT(chicken)
$expression
$expression$`Number of tests`
[1] 9893
$expression$`Sample size`
[1] 43
$covariates
AfClass ArrayName Mere Lot Pds9s Af
F :18 F10 : 1 GMB05555:10 L2:16 Min. :1994 Min. :-25.5397
L :19 F11 : 1 GMB05625: 7 L3:11 1st Qu.:2284 1st Qu.: -8.0042
NC: 6 F12 : 1 GMB05562: 5 L4: 8 Median :2371 Median : 2.7166
F13 : 1 GMB05599: 5 L5: 8 Mean :2370 Mean : 0.2365
F14 : 1 GMB05554: 4 3rd Qu.:2474 3rd Qu.: 8.6037
F15 : 1 GMB05589: 4 Max. :2618 Max. : 18.1024
(Other):37 (Other) : 8
$annotations
ID
RIGG00001: 1
RIGG00002: 1
RIGG00003: 1
RIGG00005: 1
RIGG00006: 1
RIGG00007: 1
(Other) :9887
Name
Weakly similar to Q95JC9 (Q95JC9) Basic proline-rich protein : 11
No Match : 8
Weakly similar to Q90811 (Q90811) Hypothetical 28.6 kDa protein (Fragment) : 8
Weakly similar to Q9DDJ7 (Q9DDJ7) Retinoblastoma tumor suppressor (Fragment): 8
Weakly similar to Q08525 (Q08525) Reverse transcriptase : 6
Weakly similar to Q8MW53 (Q8MW53) Precollagen-D : 6
(Other) :9846
Block Column Row Length
Min. : 1.00 Min. : 1.00 Min. : 1.00 Min. :60.00
1st Qu.:13.00 1st Qu.: 6.00 1st Qu.: 6.00 1st Qu.:70.00
Median :25.00 Median :11.00 Median :12.00 Median :70.00
Mean :24.87 Mean :11.04 Mean :11.63 Mean :69.57
3rd Qu.:37.00 3rd Qu.:16.00 3rd Qu.:17.00 3rd Qu.:70.00
Max. :48.00 Max. :21.00 Max. :22.00 Max. :75.00
>
> # Calculation of classical p-values
> ############################################
> # test on the 6th covariate:
> rawpval = raw.pvalues(chicken,x=6)
> hist(rawpval$pval)
>
> # with a supplementary covariate (third column of the covariates data frame)
> ## Not run: rawpval = raw.pvalues(chicken,x=c(3,6),test=6)
> ## Not run: hist(rawpval$pval)
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.