This two-day intensive boot camp starts with a fast-paced training session on single cell data collection and basic analysis workflows on the first half-day, then continues with in-depth sessions on advanced methods for phenotyping single cell populations using systems-biology approaches. Led by a team that invented several of the methods used in network biology and single-cell transcriptome analysis, we demonstrate how to use network models to convert gene expression profiles into protein activity profiles, and how to transfer knowledge between established bulk datasets and novel single-cell data. We expect that, during this hands-on workshop, participants will acquire enough knowledge to plan and perform scRNAseq analyses in real-world applications.
By the end of the workshop, participants will be familiar with the following topics:
- Gene Expression Analysis of scRNA data (pre-processing, quality control, filtering, normalization)
- Cluster Analysis
- Cell Type Identification
- Regulatory Network Analysis
- Master Regulator Analysis
Audience and Requirements
Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are a few requirements to attend this training:
- Each participant must have an introductory background in statistics.
- Each participant must be familiar with basic R & Python.
- Each participant must have a free, basic RStudio Cloud account prior to the first day of the workshop for lab sessions.
- (Extra) Each participant will benefit from having a free basic Google/Gmail account to access Google Colab for additional material.
Additional Information
