Background: Functional genomics aims to decipher gene function by observing cellular changes when specific genes are disrupted using CRISPR technology. However, these experiments are limited by scalability, as comprehensive CRISPR screens require extensive resources, involving millions of cells and thousands of sgRNAs, making large-scale studies challenging. We propose a novel approach with "CRISPR lossy compression" to reduce the complexity of CRISPR screens by focusing on key genetic nodes that can infer genome-wide phenotypes.
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