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Why isn't nrBreaks := rand.Poisson(rate) sufficient? You're drawing from a poisson as an approximate binomial, under the assumption that breakpoints occur at any position with some constant probability. But the number of breakpoints under this scheme is non-linear in the transcript length, which is difficult to account for:
Second, possibly related:
FRAG:
fori:=0; i<len(breaks)-2; i++ {
This skips the last fragment, resulting in a depletion of fragments at the 3' end of the transcript. Was that intentional? Is there reason to believe that fragments can't be primed after the last breakpoint?
Sorry to bombard you with super-specific questions. Rlsim is by far the best rna-seq simulator I've used, and I want to make sure it's behavior in these cases is plausible before I either try to account for it in my quantification model, or make tweaks to rlsim.
The text was updated successfully, but these errors were encountered:
There are two implementation details of
FragAfterPrim
, that aren't necessarily bugs, but I don't quite understand. I'm hoping you can shed some light.First is this:
Why isn't
nrBreaks := rand.Poisson(rate)
sufficient? You're drawing from a poisson as an approximate binomial, under the assumption that breakpoints occur at any position with some constant probability. But the number of breakpoints under this scheme is non-linear in the transcript length, which is difficult to account for:Second, possibly related:
This skips the last fragment, resulting in a depletion of fragments at the 3' end of the transcript. Was that intentional? Is there reason to believe that fragments can't be primed after the last breakpoint?
Sorry to bombard you with super-specific questions. Rlsim is by far the best rna-seq simulator I've used, and I want to make sure it's behavior in these cases is plausible before I either try to account for it in my quantification model, or make tweaks to rlsim.
The text was updated successfully, but these errors were encountered: