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StochasticGene.jl

A Julia package for simulating and fitting stochastic models of gene transcription to experimental data.

Overview

StochasticGene.jl is designed to analyze various types of experimental data including:

  • Distributions of mRNA counts per cell (e.g., single molecule FISH (smFISH) or single cell RNA sequencing (scRNA-seq) data)
  • Image intensity traces from live cell imaging
  • Dwell time distributions of reporters (e.g., MS2 or PP7) imaged in live cells
  • Combinations of the above data types

The package implements stochastic (continuous Markov) models with:

  • Arbitrary number of G (gene) states
  • R (pre-RNA) steps
  • S splice sites (up to R)
  • Reporter insertion step

Key Features

  • Flexible Model Specification

    • Support for multiple alleles of the gene in the same cell
    • Configurable reporter visibility at specific R steps
    • Coupling between genes/alleles
    • Support for both exon and intron reporter constructs
    • Classic telegraph models with arbitrary numbers of G states
    • Multiple simultaneous reporters (e.g., for introns and transcription factors)

  • Advanced Capabilities

    • Parallel processing capabilities
    • Scalable from laptop to cluster computing
    • Bayesian parameter estimation
    • MCMC fitting
    • Comprehensive result analysis

Quick Start

using StochasticGene

# Set up directory structure
rna_setup("scRNA")

# Fit a simple two-state model
fits, stats, measures, data, model, options = fit(nchains=4)

Documentation Structure

System Requirements

  • Julia version 1.9.3 or higher
  • Required packages will be automatically installed
  • For large datasets: Multiprocessor system recommended

Support

Citation

If you use StochasticGene.jl in your research, please cite:

  • Rodriguez et al. Cell (2018)
  • Wan et al. Cell (2021)
  • Trzaskoma et al. Science Advances (2024)

License

This package is licensed under the MIT License.