Estimating the Causal Effects of T Cell Receptors

תקציר מקורי באנגליתarXiv:2410.14127v2 Announce Type: replace-cross Abstract: A central question in human immunology is how a patient's T cell receptors impacts disease. Here, we introduce a method to infer the causal effects of T cell receptor (TCR) sequences on patient outcomes using observational TCR sequencing data and clinical outcomes data. Our approach corrects for unobserved confounders, such as a patient's environment and life history, using the patient's pre-selection TCR repertoire. This pre-selection repertoire is generated by a programmed stochastic recombination process, V(D)J recombination, which provides a natural experiment. We first derive a causal identification result that leverages biological theory to semiparametrically constrain a hierarchical causal model, enabling causal inference. We