MS2 Reporter Analysis

This example demonstrates how to analyze live cell imaging data using MS2 reporters.

Setup

First, let's set up our project directory and load the package:

using StochasticGene

# Create project directory
rna_setup("ms2_example")
cd("ms2_example")

Data Preparation

Place your MS2 reporter image data in the data/ directory. The data should be in a format compatible with the package (see Data Types for details).

Model Definition

We'll fit a model with:

• 2 gene states (G=2)
• 1 pre-RNA step (R=1)
• MS2 reporter insertion at the first step

# Define model parameters
G = 2  # Number of gene states
R = 1  # Number of pre-RNA steps
transitions = ([1,2], [2,1])  # Gene state transitions

Fitting the Model

Now we can fit the model to our MS2 data:

# Fit the model
fits, stats, measures, data, model, options = fit(
    G = G,
    R = R,
    transitions = transitions,
    datatype = "trace",
    datapath = "data/",
    gene = "MS2",
    datacond = "CONTROL"
)

Analyzing Results

Let's examine the fitting results:

# Print basic statistics
println(stats)

# Plot the results
using Plots
plot(fits)

# Fit writes rates, measures, and parameter statistics under `resultfolder`.

Model Interpretation

The fitted model provides:

• Gene state transition rates
• Transcription rates
• Reporter maturation rates
• Model likelihood and fit statistics

Advanced Analysis

Time Series Analysis

# For fitted key-based trace folders, use:
write_traces_key("results/my-ms2-run")

Burst Analysis

# For burst summaries, run fits with `burst=true` and inspect the burst output
# files written by `fit`.

Next Steps

• Try fitting models with multiple reporters
• Experiment with different reporter configurations
• Compare results across different genes

For more advanced examples, see:

• Dual Reporter System
• Time Series Analysis
• Coupled Models