samSFS

Inferring the somatic evolution of stem cell mutations in plants

• Mutations originating in stem cells at the shoot apex often become fixed in large sectors of the plant body due to cell lineage drift during repeated branching.
• Inferring the somatic evolution of such mutations requires knowledge of the effective stem cell population size, the cellular bottleneck strength during branch initiation, and the mutation rate.
• This repository provides statistical tools to estimate these parameters directly from cell-layer-specific DNA sequencing data.

Note: Details regarding the biological framework and theoretical model can be found in Johannes, bioRxiv https://doi.org/10.1101/2025.01.13.632685.

---

Installation

To get started, clone the repository to your project folder:

git clone https://github.com/jlab-code/samSFS.git
cd samSFS

---

Recommended: Use as an RStudio Project

This project is structured to work cleanly as an RStudio Project:

1. Open RStudio.
2. Go to File → Open Project...
3. Select the samSFS/ folder.
4. This ensures your working directory is set correctly and scripts will run without modification.

You can also create a .Rproj file in the repo for convenience.

---

Alternative: Manual R Console Use

If you're not using RStudio, load the code manually in R:

# Load all core functions
files <- list.files("R", full.names = TRUE)
sapply(files, source)

# Load C++ backend
Rcpp::sourceCpp("src/simulate_processes.cpp")

---

Project Structure

samSFS/
├── R/                  # Core R functions (contains all modular R core functions)
├── src/                # C++ simulation engine
├── data/               # Input data (contains example data from Goel et al. 2024)
├── results/            # Output folders created by scripts
├── demo/               # Demo scripts for real and simulated analyses
├── README.md           # Project documentation

---

Real Data Demo

To run the full pipeline on real observed data:

Option 1: Open as RStudio Project (Recommended)

1. Clone the repo.
2. In RStudio, go to File → Open Project and select the samSFS/ folder.
3. Open demo/test_real_data.R and run the code line-by-line.
4. Output will be saved to: results/real_data_results/

Option 2: In RStudio (without project)

1. Open the samSFS folder in RStudio.
2. Open and run the file demo/test_real_data.R.
3. Run line-by-line to understand each step.
4. Results will be saved to: results/real_data_results/

Option 3: From Terminal

cd samSFS
Rscript demo/test_real_data.R

---

Simulated Data Demo

To run a full simulation + inference pipeline:

Option 1: Open as RStudio Project (Recommended)

1. Clone the repo.
2. In RStudio, go to File → Open Project... and select the samSFS/ folder.
3. Open demo/test_simulations.R and run the code line-by-line.
4. Output will be saved to: results/test_simulation_output/

Option 2: In RStudio (without project)

1. Open the samSFS folder in RStudio.
2. Open and run the file demo/test_simulations.R.
3. Step through each line to understand simulation and inference steps.
4. Output will be saved to: results/test_simulation_output/

Option 3: From Terminal

cd samSFS
Rscript demo/test_simulations.R

---

Notes

• All demo scripts assume you run them from the root samSFS/ folder.
• Each script sets thread usage, simulation parameters, and output paths explicitly.
• Results folders are automatically created during analysis.

---

Contact

For questions or collaboration, reach out via GitHub Issues or open a pull request.