Filter, plot & explore | Practical
Trainer: Wendi Bacon, Marisa Loach, Julia Jakiela, Graeme Tyson
Overview: You’ve done all the work to make a single cell matrix, with gene counts and mitochondrial counts and buckets of cell metadata from all your variables of interest. Now it’s time to fully process our data, to remove low quality cells, to reduce the many dimensions of data that make it difficult to work with, and ultimately to try to define our clusters and to find our biological meaning and insights! There are many packages for analysing single cell data – Seurat Satija et al. 2015, Scanpy Wolf et al. 2018, Monocle Trapnell et al. 2014, Scater McCarthy et al. 2017, and so forth. We’re working with Scanpy, because currently Galaxy hosts the most Scanpy tools of all of those options.
Learning objectives:
By the end of this session you will be able to:
- Interpret quality control plots to direct parameter decisions
- Repeat analysis from matrix to clustering
- Identify decision-making points
- Appraise data outputs and decisions
- Explain why single cell analysis is an iterative (i.e. the first plots you generate are not final, but rather you go back and re-analyse your data repeatedly) process
Materials:
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