Vector with gene names or dataframe which contains all information about spots on the chip
logratio
matrix with one row by gene and one column by replicate giving the logratio
fileexport
file to export the list of differentially expressed genes
minrep
minimum number of replicates to take a gene into account, minrep must be higher than 2
method
method of multiple tests adjustment for p.values
threshold
threshold of False Discovery Rate
Details
This function implements the structural model for variances described in (Jaffrezic et al., 2007).
Data must be normalized before calling the function. Matrix geneNumbers must have one of
the following formats: "matrix","data.frame","vector","character","numeric","integer".
Value
Only the number of differentially expressed genes is printed.
If asked, the file giving the list of differentially expressed genes is created
If the user creates an object when calling the function (for example "Stat=SMVar.paired(...)")
then Stat contains the information for all genes, is sorted by ascending p-values and
Stat$TestStat
gives the test statistics as described in the paper
Stat$StudentPValue
gives the raw p-values
Stat$DegOfFreedom
gives the number of degrees of freedom for the Student distribution for the test statistics
Stat$LogRatio
gives the logratios
Stat$AdjPValue
gives the adjusted p-values
Note
If the first column of the file geneNumbers contains identical names for two different spots,
these two spots are only counted once if they are both differentially expressed.
By default, the correction for multiple testing is Benjamini Hochberg with a threshold of False Discovery Rate (FDR) of 5%.
The FDR threshold can be changed, and it is also possible to choose the multiple test correction method
("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none").
To see the references for these methods, use the R-help ?p.adjust.
Author(s)
Guillemette Marot with contributions from Anne de la Foye
References
F. Jaffrezic, Marot, G., Degrelle, S., Hue, I. and Foulley, J. L. (2007) A structural mixed model for variances in differential gene expression studies. Genetical Research (89) 19:25
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(SMVar)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/SMVar/SMVar.paired.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SMVar.paired
> ### Title: Structural model for variances with paired data
> ### Aliases: SMVar.paired
> ### Keywords: methods models
>
> ### ** Examples
>
> library(SMVar)
> data(Spleendata)
> attach(Spleendata)
> SMVar.paired(SpleenGeneId,SpleenLogRatio)
[1] "125 differentially expressed gene(s)"
[1] "Warning: No file is given to save the results of the analysis"
>
>
>
>
>
> dev.off()
null device
1
>