With the increase of number of cellular parameters per flow cytometry assay, we are entering the world of big data. Dagna Sheerar will present an overview of some of the more common computational data analysis methods for these high-dimensional data sets. Computational analysis can help improve rigor and reproducibility by removing the subjectivity of the traditional pairwise manual gating strategy currently employed for most flow cytometry experiments.
This seminar will start with a review of a Nature Reviews Immunology paper published in 2016, “Computational flow cytometry: helping to make sense of high-dimensional immunology data“, followed by some published examples by researchers here at UW, and finally a discussion focusing on how to best plan experiments to leverage these computational analysis platforms.
Tuesday, January 22, 2019, 10-11am in WIMR 7001A