  Stochasticity is an indispensable aspect of biochemical processes at the
cellular level. Studies on how the noise enters and propagates in biochemical
systems provided us with nontrivial insights into the origins of stochasticity,
in total however they constitute a patchwork of different theoretical analyses.
Here we present a flexible and generally applicable noise decomposition tool,
that allows us to calculate contributions of individual reactions to the total
variability of a system's output. With the package it is therefore possible to
quantify how the noise enters and propagates in biochemical systems. We also
demonstrate and exemplify using the JAK-STAT signalling pathway that it is
possible to infer noise contributions resulting from individual reactions
directly from experimental data. This is the first computational tool that
allows to decompose noise into contributions resulting from individual
reactions.
