Contents:

causarray is a Python module for simultaneous causal inference with an array of outcomes.

Introduction

• causarray

Main functions

• Preprocessing
• Generalized confounder estimation
• Doubly-robust semiparametric inference

Tutorials (Python)

• Joint Perturb-seq Perturbation Analysis
  • Number of latent factors
  • Estimate unmeasured confounders
  • Estimate log-fold change based on counterfactuals
  • Propensity-score and positivity diagnostics
  • Treatment-specific association diagnostics
• Batch-wise causarray Analysis — Replogle-E-K562
  • 1. Load data
  • 2. Prepare causarray inputs
  • 3. Number of latent factors
  • 4. Batch fitting with gcate_lfc_batch
  • 5. Results
  • 6. Summary
• Case-Control Study: How Alzheimer’s Disease Affects Gene Expression
  • Why pseudo-bulk?
  • Load data
  • Exploratory data analysis
  • Prepare causarray inputs
  • Number of latent factors
  • Estimate latent confounders (GCATE)
  • Propensity-score and positivity diagnostics
  • Estimate log-fold changes
  • Visualise results
  • Summary

Tutorials (R)

• Perturb-seq Tutorial (R)

Release Notes

• Changelog