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.

Aaron, Gordon: many thanks.