Causal identification of single-cell experimental perturbation effects with CINEMA-OT

Recent advancements in single-cell technologies allow characterization of experimental perturbations at single-cell resolution. While methods have been developed to analyze such experiments, the application of a strict causal framework has not yet been explored for the inference of treatment effects at the single-cell level. In this work, we present a causal inference-based approach to single-cell perturbation analysis, termed CINEMA-OT (Causal INdependent Effect Module Attribution + Optimal Transport). CINEMA-OT separates confounding sources of variation from perturbation effects to obtain an optimal transport matching that reflects counterfactual cell pairs. These cell pairs represent causal perturbation responses permitting a number of novel analyses, such as individual treatment effect analysis, response clustering, attribution analysis, and synergy analysis. We benchmark CINEMA-OT on an array of treatment effect estimation tasks for several simulated and real datasets and show that...,

The rhinovirus infection data:
Primary human bronchial epithelial cells from healthy adult donors were obtained from a commercial vendor (Lonza) and cultured at air-liquid interface according to the manufacturer's instructions (Stem Cell Technologies) using reduced hydrocortisone. Cells were kept at air-liquid interface for 4 weeks before experiment; maturation of beating cilia and mucus production was confirmed using light microscope. Cells were then infected with mock or 105 PFU human rhinovirus 1A per organoid, with or without exposure to 2% cigarette smoke extract (CSE). Single cell suspension is collected by trypsin digestion at 5 days post-infection and submitted to single cell RNA sequencing using The 10X Genomics single-cell 3′ protocol.
The combinatorial interferon stimulation data: 

The study was approved by Institutional Review Boards at Yale University (following Yale melanoma skin SPORE IRB protocol). Healthy donors consented to donation of peripheral blood for resear..., Both the 10x format count matrix files and the preprocessed Scanpy objects are provided for both datasets. , # Dataset Readme

## The Rhinovirus infection dataset

The raw count matrix files are \"041719\_RVCSE\_filtered\_feature\_bc\_matrix.zip\", \"041719\_RV\_filtered\_feature\_bc\_matrix.zip\", \"041719\_MOCK\_filtered\_feature\_bc\_matrix.zip\", and \"041719\_CSE\_filtered\_feature\_bc\_matrix.zip\". The preprocessed Scanpy object is provided as \"rvcse\_221021.h5ad\".

## The combinatorial interferon stimulation dataset

The raw count matrix files are \"H1D2.zip\", \"H1D7.zip\", \"H2D2.zip\", \"H2D7.zip\", \"H3D2.zip\", and \"H3D7.zip\". The integrated raw Scanpy object is provided as \"Integrated\_raw.h5ad\". The preprocessed Scanpy object is provided as \"Integrated\_.h5ad\".