About this Class

This 3-hour seminar is tailored for biologists, data analysts, and researchers who are eager to dive into the essentials of computational flow cytometry analysis using R. Flow cytometry is a crucial technique in cell biology, enabling the quantitative analysis of cell populations for a deeper understanding of health. The seminar focuses on the computational data analysis step, guiding participants through the basics of analyzing and understanding flow cytometry data. It includes hands-on code demonstrations and a follow-along activity, utilizing popular R packages for flow cytometry analysis such as flowCore, flowAI, ggcyto, among others, to load, visualize, and analyze .fcs files effectively.

Target Audience

- Researchers and students in cell biology, immunology, and related fields

- Biomedical researchers interested in learning computational data analysis

- Data analysts and bioinformaticians exploring flow cytometry

Prerequisites

- Basic understanding of cell biology and flow cytometry concepts

- Some familiarity with R programming is helpful but not required Objectives

- Load and visualize .fcs files in R

- Understand the basics of quality control and data transformation for flow cytometry data

- Perform automated gating and basic statistical analysis using R packages

- Identify resources for further learning in computational flow cytometry Materials and Resources

- Access to presentation slides and R scripts used during the demonstration

- Sample .fcs files for the follow-along activity

- A curated list of resources for further study in computational flow cytometry analysis

Speaker:

Gabriel Rosenfeld serves as Lead of Data Science in the Science Support Section in Bioinformatics and Computational Bioscience Branch (BCBB). He also contributes as subject matter expert to the TB Portals program, a trans-national partnership to use real-world data to study drug-resistant tuberculosis. He joined NIAID as a Presidential Management Fellow (PMF) in 2013, spent several years in industry, and joined BCBB in 2020 to use data science to help advance collaborators’ research projects.

Individuals with disabilities who need reasonable accommodation to participate in this event should contact Karlynn Noble at karlynn.noble@nih.gov.