Abstract
AbstractAs the dimensionality, throughput, and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas.jl: an interactive web application that bridges the user-friendly environment of FlowJo and computational tools in Julia developed by the scientific machine learning community. We demonstrate the capabilities of FlowAtlas using a novel human multi-tissue, multi-donor immune cell dataset, highlighting key immunological findings.
Publisher
Cold Spring Harbor Laboratory
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