[BioC] Paired data for DEseq2: Multifactorial design

[Sindre Lee]

Hi!
I have two groups at two time points. And the samples are the same in 
both time points. I have run this in DESeq2:

sampleFiles <- 
list.files(path="/Volumes/timemachine/HTseq_DEseq2",pattern="*.txt");
status <- factor(c(rep("Healthy",26), rep("Diabetic",22)))
timepoints = 
as.factor(c(1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2));
sampleTable <- data.frame(sampleName = sampleFiles, fileName = 
sampleFiles, status=status, timepoints=timepoints);
directory <- c("/Volumes/timemachine/HTseq_DEseq2/");
des <- formula(~timepoints+status);
ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, 
directory = directory, design= des);
ddsHTSeq

This is however not correct.

When looking at the Limma manual page 49: 
http://www.bioconductor.org/packages/2.12/bioc/vignettes/limma/inst/doc/usersguide.pdf

This example is perfect for my experiment, but "Tissue = A or B" should 
be "Timepoint = 1 or 2".

So timepoint = 1 or 2 = Paired data, and Disease vs Normal = unpaired 
data.

I want to compare both within and between samples, so how can I do this 
in DESeq2?

> sampleTable
    sampleName fileName   status timepoints
1    D104.txt D104.txt  Healthy          1
2    D121.txt D121.txt  Healthy          1
3    D153.txt D153.txt  Healthy          1
4    D155.txt D155.txt  Healthy          1
5    D161.txt D161.txt  Healthy          1
6    D162.txt D162.txt  Healthy          1
7    D167.txt D167.txt  Healthy          1
8    D173.txt D173.txt  Healthy          1
9    D176.txt D176.txt  Healthy          1
10   D177.txt D177.txt  Healthy          1
11   D179.txt D179.txt  Healthy          1
12   D204.txt D204.txt  Healthy          1
13   D221.txt D221.txt  Healthy          1
14   D253.txt D253.txt  Healthy          2
15   D255.txt D255.txt  Healthy          2
16   D261.txt D261.txt  Healthy          2
17   D262.txt D262.txt  Healthy          2
18   D267.txt D267.txt  Healthy          2
19   D273.txt D273.txt  Healthy          2
20   D276.txt D276.txt  Healthy          2
21   D277.txt D277.txt  Healthy          2
22   D279.txt D279.txt  Healthy          2
23   N101.txt N101.txt  Healthy          2
24   N108.txt N108.txt  Healthy          2
25   N113.txt N113.txt  Healthy          2
26   N170.txt N170.txt  Healthy          2
27   N171.txt N171.txt Diabetic          1
28   N172.txt N172.txt Diabetic          1
29   N175.txt N175.txt Diabetic          1
30   N181.txt N181.txt Diabetic          1
31   N182.txt N182.txt Diabetic          1
32   N183.txt N183.txt Diabetic          1
33   N186.txt N186.txt Diabetic          1
34   N187.txt N187.txt Diabetic          1
35   N188.txt N188.txt Diabetic          1
36   N201.txt N201.txt Diabetic          1
37   N208.txt N208.txt Diabetic          1
38   N213.txt N213.txt Diabetic          2
39   N270.txt N270.txt Diabetic          2
40   N271.txt N271.txt Diabetic          2
41   N272.txt N272.txt Diabetic          2
42   N275.txt N275.txt Diabetic          2
43   N281.txt N281.txt Diabetic          2
44   N282.txt N282.txt Diabetic          2
45   N283.txt N283.txt Diabetic          2
46   N286.txt N286.txt Diabetic          2
47   N287.txt N287.txt Diabetic          2
48   N288.txt N288.txt Diabetic          2

The commands used in Limma (still at page 49):

targets <- 
readTargets("/Volumes/timemachine/HTseq_DEseq2/Targets.rtf");
Treat <- factor(paste(targets$status,targets$timepoints,sep="."));
design <- model.matrix(~0+Treat);
colnames(design) <- levels(Treat)

So how can I create the "Targets.rtf" file? And is these commands the 
same when using DESeq2?

Thank you so much!