Question: Standard errors of fitted values from glmFit in edgeR
0
2.9 years ago by
Rothamsted Research
david.hughes0 wrote:

We use edgeR for its GLM fitting.

When we present lists of differentially-expressed genes, colleagues ask to see the raw expression data, sometimes for all replicates.   We usually show the counts-per-million of the fitted data: eg.

class(y)[1]          #”DGEList”

fit <- glmFit(y, design, …)

cpm(fit\$fitted.values)

These values are the same for all replicates of given sample.

Colleagues then ask to see the standard error of the fitted values.  Can we estimate the standard errors from the object produced by glmFit?  Even an approximation would help.  Grateful for any suggestions.

edger standard error glmfit • 678 views
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modified 2.9 years ago • written 2.9 years ago by david.hughes0

Aaron, Gordon: many thanks.

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Answer: Standard errors of fitted values from glmFit in edgeR
0
2.9 years ago by
Aaron Lun23k
Cambridge, United Kingdom
Aaron Lun23k wrote:

No.

For more details, check out this post from Gordon:

A: Confidence intervals on edgeR logFC

If you want standard errors, use limma and voom instead.

ADD COMMENTlink written 2.9 years ago by Aaron Lun23k
Answer: Standard errors of fitted values from glmFit in edgeR
0
2.9 years ago by
Gordon Smyth37k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth37k wrote:

To plot individual expression values for a given gene, we usually use CPM values from cpm(y) or RPKM values from rpkm(y). Or alternatively cpm(y, log=TRUE, prior.count=3) or rpkm(y, log=TRUE, prior.count=3).

You could attach conventional standard error values to these plots (SE = s/sqrt(n)), although such naive standard errors may misrepresent (usually understate) the true statistical significant between the groups.

ADD COMMENTlink written 2.9 years ago by Gordon Smyth37k
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