Brieflow: An Integrated Computational Pipeline for High-Throughput Analysis of Optical Pooled Screening Data

Brieflow:用于高通量分析光学池化筛选数据的集成计算流程

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Abstract

Optical pooled screening (OPS) has emerged as a powerful technique for functional genomics, enabling researchers to link genetic perturbations with complex cellular morphological phenotypes at unprecedented scale. However, OPS data analysis presents challenges due to massive datasets, complex multi-modal integration requirements, and the absence of standardized frameworks. Here, we present Brieflow, a computational pipeline for end-to-end analysis of fixed-cell optical pooled screening data. We demonstrate Brieflow's capabilities through reanalysis of a CRISPR-Cas9 screen encompassing 5,072 fitness-conferring genes, processing more than 70 million cells with multiple phenotypic markers. Our analysis reveals functional gene relationships that were missed in the original study, uncovering coherent biological insights related to mitochondrial function, mRNA processing, vesicular trafficking, and MYC transcriptional control, amongst others. The modular design and open-source implementation of Brieflow facilitates the integration of novel analytical components while ensuring computational reproducibility and improved performance for the use of high-content phenotypic screening in biological discovery.

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