Pooled CRISPR Screen Analysis

Pooled CRISPR Screen Analysis

Analyze pooled CRISPR screens with single-cell RNA-seq readout using a tiered workflow: fast screening → target validation → rigorous differential expression.

When to Use This Skill

Use this skill when you have:

• ✅ Pooled CRISPR screens with scRNA-seq (Perturb-seq, CROP-seq, CRISPRi/a)
• ✅ 10X Feature Barcoding data (sgRNA captured as feature barcodes)
• ✅ Multi-library experiments with biological replicates
• ✅ sgRNA-to-cell mapping files (already assigned)

Don't use this skill for:

• ❌ Arrayed CRISPR screens (separate wells per perturbation) → use bulk RNA-seq DE skills
• ❌ Non-transcriptional readouts (e.g., protein, flow cytometry)
• ❌ Data without sgRNA assignments → use CellRanger or CROP-seq pipeline first

Quick Start (Example Data)

Test this skill with a real CRISPRi Perturb-seq dataset (~10 minutes):

from load_example_data import load_example_data
data = load_example_data()  # Downloads Papalexi 2021 (~140MB, cached after first run)

adata_list = data['adata_list']  # List of AnnData objects (one per batch)
mapping_files = data['mapping_files']  # sgRNA mapping files

What you get:

• Dataset: Papalexi & Satija 2021 ECCITE-seq CRISPRi screen (THP-1 cells)
• Size: ~20,700 cells x 18,649 genes across 4 batches
• Perturbations: 25 target genes (~4 guides each) targeting immune checkpoint regulators + non-targeting controls
• Screen type: CRISPRi (expected knockdown direction: down)
• Reference: Papalexi et al. (2021) Nature Genetics 53:322-331

For offline testing: Use load_example_data(dataset='demo') for a small synthetic dataset.

For your own data: Replace with your 10X feature-barcode matrices and sgRNA mapping files (see Inputs).

Installation

Core packages (required):

# Create conda environment
conda create -n crispr-screen python=3.8
conda activate crispr-screen

# Install packages
pip install scanpy==1.9+ anndata==0.8+ pandas numpy scipy
pip install scikit-learn  # For outlier detection
pip install diffxpy  # For differential expression