- Find Published Data
- Contribute and Publish Data
- Download Published Data
- Analyze Public Data
- Annotate and Analyze Your Data
- Join the CellxGene User Community
- Cite cellxgene in your publications
- Frequently Asked Questions
- Learn About Single Cell Data Analysis
Learn About Single Cell Analysis
While we worked hard to create a large data resource, we realized that there are educational opportunities afforded by having such a large collection of data. We are thinking through how to best leverage the opportunities this presents, but in the meantime if you are just getting started on learning about single cell analysis and data interpretation, we’ve compiled the following resources as a great place to get started:
Starting single cell RNA-seq analysis - EMBL-EBI Training: This course utilizes Galaxy pipelines, an online open-access resource that allows even the most computer-phobic bench scientists to analyze their biological data. Participants will be guided through the droplet-based scRNA-seq analysis pipelines from raw reads to cell cluster comparisons using data extracted from the Single Cell Expression Atlas. In addition to running a basic pipeline, participants will explore the variety of options within the Galaxy resource and individually analyze a given dataset. The results will be compared across the cohort to assess reproducibility and demonstrate the effect of analytical choice on research output. Finally, participants will learn about data submission, resources, and standards within the single cell field.
Cellular Genetics scRNA-seq analysis course - Sanger Institute: The material found in the course is meant to be used for anyone interested in learning about computational analysis of scRNA-seq data. The number of computational tools is increasing rapidly, and we are doing our best to keep up to date with what is available.