BrainAWG-Analysis

This repository contains analysis.py, a Python script for analyzing OSDR brain datasets (e.g., OSD-255 rodent brain RNA-seq from spaceflight). The script uses pandas for data cleaning, matplotlib for visualizing gene expression changes due to microgravity, and includes a hardware tie-in that models brain resilience impacts from radiation exposure and simulates shielding effects. The shielding simulation uses numpy (scipy compatible patterns) to model radiation dose reduction via hardware materials and links the predicted dose reduction to gene expression impact scores. It also includes optional Biopython-based FASTA annotation and notes potential for integrating with LEIA project tools from Jessica Lee.

What it does

• Load a counts matrix and sample metadata exported from OSDR datasets.
• Clean and normalize counts, then compute microgravity vs ground log2 fold changes.
• Visualize top gene expression changes due to microgravity.
• Simulate radiation dose reduction from shielding materials and map the predicted dose to gene expression impacts and a brain resilience index.
• Optionally annotate gene IDs with FASTA-derived sequence statistics using Biopython.

Usage

python analysis.py \
  --counts path/to/counts.csv \
  --metadata path/to/metadata.csv \
  --outdir outputs \
  --simulate-shielding \
  --shielding-material Polyethylene \
  --shielding-thickness-cm 5

To run a self-contained demo with synthetic data:

python analysis.py --demo --simulate-shielding

Data expectations

• The counts file should have gene IDs in the first column and sample IDs as subsequent columns.
• The metadata file should include columns sample_id and condition (override with --sample-column and --condition-column if needed).
• Conditions should include labels for microgravity and ground controls (defaults: microgravity and ground).