Direct simulation of a stochastically driven multi-step birth-death process

Creators: Gorin, Gennady; Pachter, Lior

Abstract

The description of transcription as a stochastic process provides a framework for the analysis of intrinsic and extrinsic noise in cells. To better understand the behaviors and possible extensions of existing models, we design an exact stochastic simulation algorithm for a multimolecular transcriptional system with an Ornstein-Uhlenbeck birth rate that is implemented via a special function-based time-stepping algorithm. We demonstrate that its joint copy-number distributions reduce to analytically well-studied cases in several limiting regimes, and suggest avenues for generalizations.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Version 1 - January 21, 2021; Version 2 - March 3, 2021. The DNA, pre-mRNA, and mature mRNA illustrations used in Figure 2, reproduced from [34], are derivatives of the DNA Twemoji by Twitter, Inc., used under CC-BY 4.0. G.G. and L.P. were partially funded by NIH U19MH114830. Code availability: MATLAB code that can be used to reproduce Figures 4-S3, including the simulation and plotting routines, is available at https://github.com/pachterlab/GP_2021. The authors have declared no competing interest.

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Submitted - 2021.01.20.427480v2.full.pdf

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