What: Hands-on Workshop for common workflows for the analysis of High Parameter Flow & Spectral Cytometry data sets.
Date: Thursday, November 21, 2024, WIMR 7001A
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: UWCCC Flow Cytometry Laboratory
Prerequisites:
Laptop with FlowJo Version 10.10 and R Version 4.4 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 Wednesday, November 20, 2021 in WIMR 7005 from 1pm-4pm. Instructions for installing R and Plugins and R integration with FlowJo are posted here: https://drive.google.com/file/d/1eX5rIJa0ipuIz41DxUIGdJRQgQBaQefe/view?usp=sharing. 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.