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Activity Number: 34
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #319870
Title: A Generalized Estimating Equations Framework for the Analysis of Intracellaur Cytokine Staining Data
Author(s): Amit Meir* and Raphael Gottardo and Greg Finak
Companies: University of Washington and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
Keywords: estimating equations ; Flow Cytometry ; shrinkage ; mixture modeling ; cytokine ; overdispersioh

Intracellular Cytokine Staining (ICS) - a type of cytometry experiment used to measure cytokine production at the single cell level - is an important measure used in immune monitoring and vaccine development. A well known challenge in analyzing flow cytometry data is that they are prone to batch and technical variation, but also produce many correlated features (cell subsets). These effects are often ignored; cell subsets are treated independently, counts are modeled as proportions, and batch effects are not systematically accounted for. We propose a generalized estimating equation modeling framework for analyzing cytometry count data, allowing for the screening of cell populations while accounting for both technical and biological nuisance factors. We account for the overdispersion often observed when modeling small counts by using the beta-binomial distribution. To account for the within subject dependence we estimate an unstructured working correlation and robust standard errors, which are then shrunk towards model based estimates to increase stability. We demonstrate our methodology by applying it to experimental assays measuring cytokine expression at the single-cell level.

Authors who are presenting talks have a * after their name.

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