Question: edgeR DGEList and design matrix
0
gravatar for ctstackh
13 days ago by
ctstackh0
ctstackh0 wrote:

I'm new to edgeR and trying to perform differential expression for my samples, but having difficulties getting started. I have 8 pairs of samples most with 3 replicates each (1 replicate each from 2 groups had to be thrown out because they didn't pass QC).

So in general, each pair consists of 3 control and 3 treated biological replicates.

What I've tried to do is this:

group <- factor(c(1,1,1,1,1,1,2,2,2,2,2,2,3,3,3,3,3,3,4,4,4,4,4,4,5,5,5,5,5,6,6,6,6,6,6,7,7,7,7,7,8,8,8,8,8,8))
treat <- factor(c(1,1,1,2,2,2,1,1,1,2,2,2,1,1,1,2,2,2,1,1,1,2,2,2,1,1,1,2,2,1,1,1,2,2,2,1,1,2,2,2,1,1,1,2,2,2))
## Set up y and design
y <- DGEList(counts = x, group = group)
y <- calcNormFactors(y)
design <- model.matrix(~treat+group, data = y$samples)
y <- estimateDisp(y,design)

However, when I run estimateDisp I get the following error:

Error in lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,  : 
  newsplit: out of vertex space

Am I setting up the DGEList object and design matrix correctly? If not, what should I do differently?

Thanks! -Christian

edger dge • 92 views
ADD COMMENTlink modified 13 days ago by Yunshun Chen390 • written 13 days ago by ctstackh0
Answer: edgeR DGEList and design matrix
0
gravatar for Gordon Smyth
13 days ago by
Gordon Smyth38k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth38k wrote:

To use edgeR pipelines, you need to first filter out non-expressed or very low expressed genes using filterByExpr(). See the User's Guide or one of the examples:

https://bioconductor.org/packages/release/workflows/vignettes/RnaSeqGeneEdgeRQL/inst/doc/edgeRQL.html

The error you report does not have anything to do with the DGEList or the design matrix. I have never myself seen this error triggered in 10 years of using edgeR and I've only heard of it reported once before:

https://support.bioconductor.org/p/84696/

The error comes from the locfit package, which is called by edgeR to fit a lowess curve, and I think the error will go away if you filter your data as recommended.

Alternatively, running estimateDisp with trend.method="loess" will also make the error go away at the cost of making estimateDisp very slightly slower.

ADD COMMENTlink modified 13 days ago • written 13 days ago by Gordon Smyth38k

keep <- filterByExpr(x)

x <- x[keep,]

solved the issue!

I'm still not sure what my design should be: treat+group, group+treat, group*treat, group:treat? I want to compare treated and untreated within groups, but I also want to compare all treated vs all untreated. Would I use et for these comparisons?

Thanks! Christian

ADD REPLYlink written 13 days ago by ctstackh0

Your design matrix is correct as it is.

For the filtering, you should use

fillterByExpr(x, group=treat)

or

filterByExpr(y, group=treat)
ADD REPLYlink modified 12 days ago • written 12 days ago by Gordon Smyth38k
Answer: edgeR DGEList and design matrix
0
gravatar for Yunshun Chen
13 days ago by
Yunshun Chen390
Australia
Yunshun Chen390 wrote:

Is your x a count matrix?

If so, have you performed filtering? Lowly expressed genes (especially with zero counts across all samples) can cause problems in dispersion estimation. You can perform filtering using the filterByExpr() function.

ADD COMMENTlink modified 13 days ago • written 13 days ago by Yunshun Chen390
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