DOI: 10.5061/dryad.4xgxd25g1
title: Causal identification of single-cell experimental perturbation effects with CINEMA-OT

description: 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 it
 outperforms other single-cell perturbation analysis methods. Finally, we
 perform CINEMA-OT analysis of two newly-generated datasets: (1) rhinovirus
 and cigarette smoke-exposed airway organoids, and (2) combinatorial
 cytokine stimulation of immune cells. In these experiments, CINEMA-OT
 reveals potential mechanisms by which cigarette smoke exposure dulls the
 airway antiviral response, as well as the logic that governs chemokine
 secretion and peripheral immune cell recruitment.
description: 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 research use. Human
 PBMC were isolated using Lymphoprep density gradient medium (STEMCELL).
 PBMC were plated at 1 million cells per ml and stimulated with 1000U/ml
 human IFNα2 (R&D systems), 1000U/ml human IFNβ (pbl assay science
 11415), 1000U/ml human IFNγ (pbl assay science), 1ug/ml human IFN-III
 /IL-29 (R&D systems), 100ng/ml human IL-6 (NCI Biological
 Resources Branch Preclinical Biologics Repository), 20ng/ml human TNFα
 (R&D systems), and combinatorial cytokines IFNβ + IL-6, IFNβ +
 TNFα, IFNβ+ IFNγ at indicated concentrations above for up to 48 hours.
 Single cell RNA sequencing libraries were sequenced on Illumina NovaSeq at
 read length of 150bp pair-end and depth of 300 million reads per
 sample.
description: Both the 10x format count matrix files and the preprocessed
 Scanpy objects are provided for both datasets. 
description: # 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".