In the beginning, the Flux Simulator reads the transcripts of the reference annotation and clusters genomic overlapping ones into loci.

To assign a random expression profile where not necessarily all transcripts of the reference are expressed. Expression levels are connected with the relative expression rank  by a mixed power- and exponential law of the general form

\[y=y^{k} exp^{-\frac{x}{a}-\left(\frac{x}{b}\right)^2}\]

where denotes the rank number of a gene and is the exponent of the intrinsic power law, and respectively  control the exponential decay. The Flux Simulator assigns to the transcripts in the reference annotation randomly expression ranks which then are turned into relative expression levels by the modified Zipf's Law above, which determines the initial number of molecules by multiplication with the total numbers of molecules. Default values for parameters and have been estimated for mammalian cells by non-linear fitting to expression levels observed in experimental results.

Output: The first 6 columns of the PRO_FILE

After the number of RNA molecules has been determined for each transcript, in silico expressed transcripts are assigned individual variations in transcription start and the length of the attached poly-A tail. The FLUX SIMULATOR modeles differences in transcription start are modelled by random variables under an exponential model with a mean around 10nt. During poly-adenylation in the nucleus usually 200-250 adenine residues get added to the primary transcript. Disregarding other poly-adenylation mechanisms, as cytoplasmatic polyadenylation, and the exact mechanisms of degrading processes by exo- and endonucleases, our model describes poly-A lengths by randomly sampling under a Gaussian distribution with a mean of 125nt and shape adapted s.t. >99.5% of the random variables fall in the interval [0;250].