Single-cell RNA sequencing (scRNA-seq) is a relatively new and powerful method in genomics, which enables the interrogation of whole single cellular transcriptomes. The CCR Collaborative Bioinformatics Resource (CCBR) has implemented a basic scRNA-seq workflow, based on the popular Seurat workflow, on the NIH Integrated Data Analysis Platform (NIDAP). This platform is available and free to use for all NCI researchers. The platform allows users to explore and build their analyses in a graphical environment. For researchers who are conversant in code, or who are interested in learning, all of the workflow code is easily viewable and modifiable, as well.
This course will consist of a series of video tutorials that you may work through at your own speed, followed by a live virtual Discussion class in which you can ask our instructors to clarify or expand on any topics covered in the video tutorials. You will be emailed instructions on how to begin after registration for this course ends on September 3rd. At that time, you will receive access to the tutorials and documentation, as well as a calendar invitation to your live Discussion class. Your live Discussion class will occur at 2pm on September 10th.
IT IS YOUR RESPONSIBILITY to complete ~4.5 hours of self-guided video tutorials BEFORE to your scheduled Discussion class so that you can effectively participate in the discussion.
Topics you will learn about include the theory behind scRNA-seq and many of the methodologies we use in the analysis, as well as a full tutorial on how to complete a basic scRNA-seq analysis, including filtering and QC, PCA and merging of objects, TSNE and UMAP projecctions, cell type annotation, coloring cells by gene expression or other metadata, and differential expression of genes analysis. After you complete this training, you will become eligible for further training tutorials in which you will learn how to upload your own data to the platform to begin your own analyses and gain access to workshops with our trainers to help you overcome any dataset-specific challenges that you may encounter.
PLEASE NOTE: Trainees will need their own NIH user name and password and an NIH computer capable of connecting to the secure NIH network using VPN. This is necessary to ensure the security and privacy of the data.