Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes

arXiv:2404.09119v1 Announce Type: cross
Abstract: With the evolution of single-cell RNA sequencing techniques into a standard approach in genomics, it has become possible to conduct cohort-level causal inferences based on single-cell-level measurements. However, the individual gene expression levels of interest are not directly observable; instead, only repeated proxy measurements from each individual's cells are available, providing a derived outcome to estimate the underlying outcome for each of many genes. In this paper, we propose a generic semiparametric inference framework for …

abstract arxiv become causal causal inference data evolution gene genomic genomic data genomics however inference inferences multiple observable rna sequencing standard stat.ap stat.me stat.ml type