Data Analysis Rigor and Reproducibility, Part 1: Experimental Design

Recorded On: 08/15/2019

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About the Presenter

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Dagna Sheerar, SCYM
Manager
University of Wisconsin Carbone Cancer Center (UWCCC) Flow Lab

Dagna Sheerar has been working in flow cytometry shared resource laboratories since 2000, starting out as an assistant in organizing a BSL-3 cell sorting facility at the Immunology Services Laboratory of the Wisconsin National Primate Research Center. From there, she went on to manage the Flow Lab at the University of Western Ontario for three years. In 2006, Ms. Sheerar returned to the University of Wisconsin—Madison to work in the Carbone Comprehensive Cancer Center’s Flow Cytometry Laboratory. In 2011, she was hired as the manager of the UWCCC Flow Lab. Always an active member in the flow cytometry community, Ms. Sheerar is a member of the Steering Committee for the Great Lakes International Imaging and Flow Cytometry Association and a member of the ISAC Shared Resources Laboratory Educational Task Force. As manager of the UWCCC Flow Lab, Ms. Sheerar focuses on providing researchers with the tools and support to perform rigorous and reproducible flow cytometry assays in basic research and clinical research trials.

Webinar Summary

This webinar will outline the steps and considerations in designing a successful flow cytometry assay in the context of basic research and clinical research trials. We will focus on how best to minimize variables for a robust and reproducible assay, paying attention to producing data sets well suited to downstream computational data analysis platforms.

Learning Objectives

  • Discuss the importance of working with biostatisticians in the early experimental planning stages.
  • Describe how to create criteria for sample inclusion/exclusion and building in room for sample loss.
  • Learn the importance of validating reagents and proper quality control and characterization of instrumentation.
  • Discuss how to create rigorous protocols and the importance of record keeping and annotation.
  • Expectations for the design, optimization, and standardization of assays and data analysis pipelines.

Who Should Attend

  • Researchers using flow cytometry assays in the course of their research.
  • SRL staff supporting researchers in the design, optimization, standardization, and data analysis of these research projects.
  • Computational biologists and biostatisticians performing data analyses for large-scale flow cytometry based experiments.

CMLE Credit: 1.0

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Data Analysis Rigor and Reproducibility, Part 1: Experimental Design
Recorded 08/15/2019
Recorded 08/15/2019 A CYTO U Webinar presented by Dagna Sheerar, SCYM
CMLE Evaluation Form
11 Questions
11 Questions CMLE Evaluation Form
Completion Credit
1.00 CMLE credit  |  Certificate available
1.00 CMLE credit  |  Certificate available