StochasticGene.jl

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

Current release: v1.8.3

Overview

If you install the package from the Julia registry (Pkg.add("StochasticGene")) or from GitHub, the full manual on this site includes Cluster and batch workflows — how to use makeswarm on NIH Biowulf, and how to merge single-unit fitted rates into an initial combined rate file for coupled models.

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

• Installation: How to install StochasticGene.jl
• Getting Started: Basic usage and examples
• Package overview: Project layout, results/ conventions, nomenclature (states vs steps), datatype summary, output files
• Cluster and batch workflows: Biowulf swarms, makeswarmfiles, combined rate files (create_combined_file*), and key-based runs
• API Reference: Detailed documentation of all functions and types
• Concepts: Units and models: Units vs models and the unit–model map in coupled systems
• Examples: More complex usage examples
• Contributing: How to contribute to the project

System Requirements

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

Support

• Documentation: This site
• GitHub Issues: Report bugs or request features
• Maintainers: Contact the package maintainers for specific questions

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.