I'm using limma + voom to model an expression dataset, but I'm observing a weird subset of genes where the standard deviation increases with the expression level rather than decreasing as is the case for most genes.

Any ideas for why this is occurring and/or what to do about it? I have found lots of advice regarding oddities at low-expression levels, but not this pattern. Thanks!

![enter image description here][1]

  [1]: /media/images/84921512-45ab-45b6-917b-30acaf2e
The high-variance genes probably have almost all counts equal to zero with just one or two very large non-zero counts. Normally such genes would be filtered out by `filterByExpr`.

The sort of pattern you see can also be caused by a hidden batch effect that affects a minority of genes and which is not accounted for by your design matrix.

I would start by identifying the wierd genes and examining their expression pattern, which may tell you something about quality or annotation issues with your data. Then you can either revise your filtering strategy to remove those genes or can you use `eBayes()` with `robust=TRUE` so that the high-variance genes will be isolated and their influence will be minimized.