→ Slides doi: 10.7490/f1000research.1112455.1)
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AuthorsCristel G Thomas, Northrop Grumman TS,
Elizabeth Thomson, Northrop Grumman TS,
Patrick Dunn, Northrop Grumman TS,
Henry Schaefer, ESAC, Inc,
Jeff Wiser, Northrop Grumman TS,
John C Campbell, Northrop Grumman TS
AbstractFlow cytometry is generating increasingly massive multi-dimensional datasets. Available analysis tools exist, but they require extensive human intervention and are not readily scalable for the increasing size of the datasets. More effort has recently been put into developing tools allowing automated analysis for high-throughput flow data, but they are geared toward bioinformaticians.
We are taking advantage of the Galaxy framework to create a workspace for high-throughput Flow Cytometry Data analysis that can be better understood and accessible for the average bench immunologist. We leveraged Galaxy’s innate ability to support multiple programming languages to develop a user-friendly analysis workflow allowing conversion and manipulation of flow cytometry binary data to text, clustering analysis and interactive visualization of the results. We have ported existing tools from Immport to Galaxy written in R, C or Python and created novel text manipulation tools in Python, and data interactive visualization tools in Javascript. These tools will be made freely available to the public through FlowGalaxy, which is deployed on an AWS Cloud instance.
