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Tip revision: 0dc168df0baeea977e8d8e2f8c37f41eb57a5b73 authored by Lisa Amrhein on 02 September 2019, 23:00:09 UTC
version 1.0.1
Tip revision: 0dc168d
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gillespie.R
\title{Gillespie algorithm for mRNA generating processes}
gmRNA_basic(n, r.on, r.degr)

gmRNA_switch(n, r.act, r.deact, r.on, r.degr)

gmRNA_burst(n, r.burst, s.burst, r.degr)
\item{n}{Number of observations}

\item{r.on}{Transcription rate during gene activation (Switching model)}

\item{r.degr}{mRNA degradation rate (all models)}

\item{r.act}{DNA activation rate (Switching Model)}

\item{r.deact}{DNA deactivation rate (Switching Model)}

\item{r.burst}{Bursty transcription rate (Bursting model)}

\item{s.burst}{Mean burst size (Bursting Model)}
Gillespie algorithms allow synthetic data simulation via three different
underlying mRNA generating processes: the basic process consists of a
simple death-birth model of mRNA transcription and degradation; the
switching process considers additionally gene activation and deactivation,
with mRNA transcription only happening in active gene states; the
bursting process, transcribes mRNA in bursts with geometrically distributed burst sizes.
x <- gmRNA_basic(100, 0.75, 0.001)
x <- gmRNA_switch(100, 0.23, 0.15, 0.75, 0.001)
x <- gmRNA_burst(10, 0.15, 0.75, 0.001)
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