Permutation
Jeff Leek
Dependencies
This document depends on the following packages:
library(devtools)
library(Biobase)
library(limma)
library(edge)
library(genefilter)To install these packages you can use the code (or if you are compiling the document, remove the eval=FALSE from the chunk.)
install.packages(c("devtools"))
source("http://www.bioconductor.org/biocLite.R")
biocLite(c("Biobase","limma","genefilter","jdstorey/edge"))Download the data
Here we are going to use some data from the paper Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays. that is a comparative RNA-seq analysis of different mouse strains.
con =url("http://bowtie-bio.sourceforge.net/recount/ExpressionSets/bottomly_eset.RData")
load(file=con)
close(con)
bot = bottomly.eset
pdata=pData(bot)
edata=as.matrix(exprs(bot))
fdata = fData(bot)
ls()## [1] "bot" "bottomly.eset" "con" "edata"
## [5] "fdata" "pdata" "tropical"Transform the data
Here we will transform the data and remove lowly expressed genes.
edata = log2(as.matrix(edata) + 1)
edata = edata[rowMeans(edata) > 10, ]Calculate t- or F-statistics rapidly
The genefilter package lets you compute statistics rapidly for very simple cases (two or multi-group) comparisons. These are not moderated in any way.
tstats_obj = rowttests(edata,pdata$strain)
hist(tstats_obj$statistic,col=2,xlim=c(-5,2))
We can now permute the sample labels using the sample function in R.
set.seed(135)
strain = pdata$strain
strain0 = sample(strain)
tstats_obj0 = rowttests(edata,strain0)
hist(tstats_obj0$statistic,col=2,xlim=c(-5,2))
We can now compare the observed and permuted statistics
quantile(tstats_obj0$statistic)## 0% 25% 50% 75% 100%
## -0.9629544 0.7488187 1.2858778 1.7910909 4.2376976quantile(tstats_obj$statistic)## 0% 25% 50% 75% 100%
## -4.6597753 -1.2448123 -0.7523461 -0.2523726 1.7116560More information
Permutation is widely applied and has many varieties.
- You can find different permutation approaches for more complicated study designs in teh permute package
- An alternative is bootstrapping. This is a whole major area as well. This book and the boot package are good places to start/
Session information
Here is the session information
devtools::session_info()## setting value
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## ui RStudio (0.99.447)
## language (EN)
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## tz America/New_York
##
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## BioconductorIt is also useful to compile the time the document was processed. This document was processed on: 2015-09-06.