Welcome to the third season of our Peer-to-Peer Teaching sessions. These are taught by our own community members to fill knowledge gaps and keep up with the accelerated pace at which bioinformatics grows. This season we are pleased to announce sessions covering * Image analysis methodologies (imageJ and QuPath) * Omics analysis in R and/or Python * Biomedical Data analysis using the clusters * Statistical analysis software (Prism) *Science communication (Illustrator).

This session on "Getting Started on scRNA-Seq data analysis using Scanpy and particularities of brain organoid scRNA-Seq data " was designed and will be delivered by Davide Capauto, Ph.D., from the Child Study Center, Program in Neurodevelopment and Regeneration, Vaccarino Lab.

Summary: 

The advent of the scRNA-Seq provides the opportunity for assessing the gene expression profile at single cell level within a heterogenous sample, as well as allowing the identification of minority cell subpopulations of interest that would otherwise not be detected in the classical bulk RNA-seq analysis.

In this 2-hour demonstration, we will start with a brief introduction on how to create a Ruddle account on the Yale cluster and how to start a session in the OnDemand portal using Jupyter notebook.

Then we will go through the first steps of scRNA-seq analysis using a Python-based toolkit Scanpy with a specific example of brain organoid scRNA-seq data.

This workshop is designed for: 

Biomedical researchers with none to minimal knowledge of Python programming.

You will learn how to: 

• Brief introduction on how to create a Ruddle account
• Use Ruddle account on the Yale cluster.
• Go from the scRNA-Seq 10X file to Jupyter notebook.
• Prefiltering steps (exclusion of cells with too many/few genes and high % of mitochondrial genes).
• Batch effect correction.
• Clustering. Example of an outlier identification in scRNA-Seq from brain organoids.

Requirements: 

Presentation will be shared, and you don't need to bring your own laptop!