Hi all,
I remember similar questions coming up before, but couldn’t track any down that
directly pertain to my situation.
Suppose I want to use bplapply() in a function to fit models to many features,
and I am applying over features. The models are stochastic, and I want the
results to be reproducible, and preferably use the same RNG seed for each
feature. So I could do:
fitModels <- function(object, seed=1, BPPARAM=bpparam()) {
bplapply(object, function(x) {
set.seed(seed)
fitModel(x)
}, BPPARAM=BPPARAM)
}
But the BioC guidelines say not to use set.seed() inside function code, and
I’ve seen other questions answered saying not to use “seed” as a function
parameter in this way.
Is it preferable to check and modify .Random.seed directly, or is there some
other standard way of doing this?
Thanks,
Kylie
~~~
Kylie Ariel Bemis
Khoury College of Computer Sciences
Northeastern University
kuwisdelu.github.io<https://kuwisdelu.github.io>
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