When
Where
Webinar Materials
Presentation Slides
About the Webinar
Single-cell RNA sequencing (scRNA-Seq) enables researchers to explore complex functional molecular systems cell-by-cell as well as cellular characterization of the cells. Through scRNA-Seq, researchers can see transcriptomic profiles in individual cells, which allows for the grouping of cell types based on gene expression. In this webinar, Dr. Bonnie LaFleur and doctoral student Joel Parker will demonstrate their clusTuneR package, an R package they developed which utilizes benchmarking metrics to help evaluate clustering performance for scRNA-Seq experiments. These benchmark metrics are especially helpful when applying standard scRNA-Seq pipelines, as there are many user-defined parameters that can influence your analysis results. ClusTuneR is the app package you need to help you compare observational results to experimental findings to calibrate bias in your methodology. Join us to learn about this valuable tool!
What You'll Learn
- What the clusTuneR benchmarking app is and does
- How the clusTuneR app can help you identify the user-defined parameters in your scRNA-Seq pipeline that may result in bias in your methodology
About the Presenters
Bonnie LaFleur, PhD, is a Research Professor in the R. Ken Coit College of Pharmacy, University of Arizona. Project areas include cancer, aging, pediatrics, and methods leveraging observational study designs (health services and real-world evidence designs). Most of her methodologic work is in statistical methods for precision healthcare, specifically biomarkers. Bonnie joined the Mel and Enid Zuckerman College of Public Health in 2008 as an Associate Professor. She is currently the Director of the Health Outcomes & PharmacoEconomics (HOPE) Center, and the Associate Director of the Center for Biomedical Informatics and Biostatistics.
Joel Parker is a Ph.D candidate in Biostatistics at the University of Arizona and builds statistical pipelines in Dr. Bonnie LeFleur's lab at the BIO5 Institute. His research interests include Bayesian modeling, scRNA-seq data and non-parametric modeling. While attending Arizona State University for his undergraduate degree, Joel worked for Circle K as a data analyst using Python to automate tasks and R to run regression analysis.