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Experiment Overview

Repository ID: FR-FCM-ZZLV Experiment name: Flow Cytometry Data Analysis using R (2013 Bioinformatics Workshop) MIFlowCyt score: 48.50%
Primary researcher: Josef Spidlen PI/manager: Josef Spidlen Uploaded by: Josef Spidlen
Experiment dates: 2013-06-17 - 2013-06-18 Dataset uploaded: Aug 2015 Last updated: Aug 2015
Keywords: [flow cytometry] [data analysis] [R] Manuscripts:
Organizations: BC Cancer Agency, Terry Fox Lab, Vancouver, BC (Canada)
Purpose: With the underlying technology rapidly increasing in complexity, Flow Cytometry (FCM) data analysis is becoming more crucial for biological experiments. This workshop aims to provide participants some familiarity with the open source software environment R as an analysis tool for FCM data as they explore the fundamental concepts of taking their data to diagnosis and discovery. Participants will be able to open their FCS files within R, explore their data using various visualizations, perform simple automated pre-processing tasks, quickly generate quality assurance reports to identify potential technical issues with the data, and automate simple gating strategies. As well, some basic clustering techniques will be explained and demonstrated, and new advanced analysis options presented (e.g., flowType, flowDensity, flowMeans, RchyOptimyx, flowClust3.0, SPADE, flowFP/flowBin, SamSPECTRAL). Workshop participants will come away with a better understanding of bioinformatics approaches to FCM analysis, be able to write their own analysis scripts in R to explore their FCM data, as well automate a gating strategy and record statistics of interest (e.g., proportions of cells in speci fic populations of interest).
Conclusion: See details about the workshop, slides and recorded presentations at http://bioinformatics.ca/workshops/2013/flow-cytometry-data-analysis-using-r-2013
Comments: Workshop presented by Radina Droumeva and Ryan Brinkman.
Funding: Supported by http://bioinformatics.ca/
Quality control: N/A
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