Workshop: FlowJo Analysis of High Parameter Data Sets

What: Hands-on Workshop for common workflows for the analysis of High Parameter Flow & Spectral Cytometry data sets.

Date: Friday, October 13, 2023

Time: 9am – 4pm

The seminar will start promptly at 9am, so please arrive earlier to allow time to set up your computer and workspace.

Intended Audience: Researchers currently using FlowJo to analyze flow & spectral cytometry data sets containing a minimum of 8 colors interested in utilizing computational and machine learning algorithms for data visualization and analysis. This will be a hands-on workshop providing step-by-step walk throughs of data quality control and clean up, data normalization, and dimensionality reduction algorithms utilizing a 15 color immunophenotyping data set generated by the staff of the UWCCC Flow Cytometry Lab on Cytek Aurora Spectral Cytometers.

Cost: $195.00 per person, UW Funding Strings Accepted

Class Size: Limit 10 Attendees, Wait List Available

Registration Link:  https://go.wisc.edu/99az48

Presented by: The following cores of the UW Biotechnology Center and UW Comprehensive Cancer Center; Biostatistics Resource Core (Biotech), Computational Informatics Shared Resource (UWCCC), Flow Cytometry Laboratory (UWCCC)

Prerequisites:

Laptop with FlowJo Version 10.9 and R Version 4.3 currently installed.

Mac Requirements

  • Minimum: 8GB RAM, Core II Duo Processor, MacOS 10.11 or newer, Internet connection for software license
  • Recommended: 16GB RAM, Intel i7 quad core processor

PC Requirements

  • Minimum: 8GB RAM, x86 or x64 dual core processor, Windows Vista, Internet connection for software license
  • Recommended:  16GB RAM, Intel i7 quad core processor, Windows 10

FlowJo Plugins:

  • FlowClean: Automated cleaning of flow data
  • FlowAI: Find anomalies in Flow Cytometry data
  • PeacoQC: An R based quality control algorithm to remove abnormal events from flow data
  • CytoNorm: Helps correct for technical variability within FlowJo by normalizing batches of flow data
  • CyCombine: Robust integration of single cell cytometry data sets
  • DownSample: Subset your sample in a specified event count
  • UMAP: A dimensionality reduction technique similar to t-SNE (t-SNE is native to FlowJo)
  • ClusterExplorer: Illustrates a profile of relative intensity values across parameters in flow cytometry data
  • Phonograph: Delineate clusters by unsupervised hearted-neighbots grouping of biological parameters
  • FlowSOM: Cluster using Self-Organizing Maps

A walk-in clinic providing assistance with FlowJo Plugins and R will be available to registrants on Thursday, October 12, 2023 at the UW Biotechnology Center in Room 1104. Registrants will receive instructions for installing R and Plugins and R integration with FlowJo approximately one week before class. For registrants using computers supported by their local IT, please share these instructions with your IT support. IT support is welcome to visit the walk-in clinic as needed.