getting data into DESeq2

[Gordona]

Hi there,
i've got R version 3.1.0
DESeq2 version 1.4.5

I'm trying to get my data into R to create a DESeq object and i've tried following the vignette to work out how I may put my data in instead and I feel like i'm banging my head against a brick wall.

I've got 3 reps of 6 treatments in my countData file with geneIDs in the first column.

My experimental design is in a second csv file.

What i'm missing is the ability to tell DESeq exactly what these two files contain, and then syntax to marry the two together using DESeqDataSetFromMatrix

Apologies for this entry-level question
Any tips much appreciated

Anna


Here's what i've inputted so far:
countData <- read.csv ("C:/Documents and Settings/x991064/Desktop/EXPRESSION/sporesVbase.csv", header=T, row.names=1)
> head(countData)
C1 C2 C3 W2 W4 W5 PB1 PB2 PB5 RB1 RB2 RB4 TB1
CPUR_00001.1 0 0 0 0 0 0 0 0 0 0 0 0 1
CPUR_00002.1 0 0 0 0 0 3 0 0 0 0 0 0 4
CPUR_00003.1 0 0 0 0 0 1 0 0 0 1 0 0 2
CPUR_00004.1 0 0 1 3 2 8 0 0 0 0 1 0 4
CPUR_00005.1 1 0 3 37 25 6 0 0 0 0 0 0 12
CPUR_00006.1 23 1 67 60 60 146 0 0 0 18 11 6 223
TB2 TB4 VB1 VB2 VB3
CPUR_00001.1 1 0 0 0 0
CPUR_00002.1 1 1 0 2 4
CPUR_00003.1 1 2 0 1 1
CPUR_00004.1 1 6 25 29 25
CPUR_00005.1 0 3 6 6 3
CPUR_00006.1 93 174 163 251 144
> colData <- read.csv("C:/Documents and Settings/x991064/Desktop/EXPRESSION/sporesVbaseDesign.csv")
> head(colData)
X time location treatment
1 C1 0 spores C
2 C2 0 spores C
3 C3 0 spores C
4 W2 1 germ W
5 W4 1 germ W
6 W5 1 germ W

[Michael Love]

hi Anna,

In R, you tell a function which is which by either providing the objects in the order in the help file, or by naming them.

For more information about a function you can always type ?DESeqDataSetFromMatrix.

As far as building a DESeqDataSet, in the vignette we have:

Now that we have a matrix of counts and the column information, we can construct a DESeqDataSet:

dds <- DESeqDataSetFromMatrix(countData = countData,
colData = colData,
design = ~ condition)

You are ready to go as the countData and colData are in the same order.

You can see that this is true with:

all(colnames(countData) == colData$X)

So you just need to specify the experimental design using an R formula.

This might be:

~ time + location + treatment

But the design you should specify depends on what your biological question is for this experiment.