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Updated: Jul 12, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Large-scale causal discovery using interventional data sheds light on the regulatory network architecture of blood
Brielin C Brown1,2, John A Morris1, Tuuli Lappalainen1,3,4
1New York Genome Center, New York, NY, USA.
Abstract:
Inference of directed biological networks is an important but notoriously challenging problem. We introduce inverse sparse regression (inspre), an approach to learning causal networks that leverages large-scale intervention-response data. Applied to 788 genes from the genome-wide perturb-seq dataset, inspre helps elucidate the network architecture of blood traits.
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