This academic webinar provides a comprehensive guide to analyzing single-cell RNA sequencing (scRNA-seq) data using all kinds of methods. Our speaker shall cover an overview of outputs from 10x Genomics Single Cell RNA-seq, practical downstream of scRNA-seq data analysis including quality metrics, normalization, dimensionality reduction, clustering, and differential expression analysis. The webinar aims to equip researchers with the knowledge and skills needed to interpret scRNA-seq data effectively. By the end of this webinar, you can comprehensively learn how to decipher primary outputs, why the quality control and normalization matters, how to maneuver different software and scripts and eventually, how to discover hidden mechanism in cell populations of your research.

Learning Objectives:

• Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to dissect cellular heterogeneity and understand the functional state of individual cells. The advent of 10x Genomics technology has further propelled this field, enabling us to analyze thousands of cells in a high-throughput manner.
• We will commence with an introduction to the 10x Genomics technology, discussing its methodology and outputs from single cell capture and sequencing. The webinar will then lead you into the practical aspects of scRNA-seq data analysis, covering topics such as quality control measures, normalization techniques, dimensionality reduction, clustering algorithms, and differential expression analysis.
• The objective of this webinar is not only to familiarize you with the process of scRNA-seq data analysis but also to enable you to interpret the results effectively and translate these findings into meaningful biological insights. This webinar is designed for researchers at all levels of expertise in genomics and aims to equip you with the necessary skills to navigate the landscape of scRNA-seq data.