Module: Single-Cell Analysis
This module will guide you through single-cell transcriptomics analysis in Galaxy.
Single-cell RNA-seq analysis is a rapidly evolving field at the forefront of transcriptomic research, used in high-throughput developmental studies
An introduction to scRNA-seq data analysis (Lecture)
| Description: | Single-cell RNA-seq analysis is a rapidly evolving field at the forefront of transcriptomic research, used in high-throughput developmental studies and rare transcript studies to examine cell heterogeneity within a populations of cells. The cellular resolution and genome wide scope make it possible to draw new conclusions that are not otherwise possible with bulk RNA-seq. Slides created by Mehmet Tekman. |
| Length: | 20 minutes |
| Captions: | Mehmet Tekman |
| Created: | 15 February 2021 |
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Slides:
Filter, Plot and Explore Single-cell RNA-seq Data (Demo)
| Description: | 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! |
| Length: | 30 minutes |
| Captions: | Wendi Bacon |
| Created: | 15 February 2021 |
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Tutorial:
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Demo Video
| Description: | This tutorial demonstrates the what barcodes in your sequencing data are, and how to handle them during analysis. Please work through the full tutorial yourself to get all the details. |
| Length: | 10 minutes |
| Captions: | Alireza Khanteymoori |
| Created: | 18 March 2021 |
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Demo Video
| Description: | This tutorial will take you from raw FASTQ files to a cell x gene data matrix in AnnData format. What’s a data matrix, and what’s AnnData format? Well you’ll find out! Importantly, this is the first step in processing single cell data in order to start analysing it. |
| Length: | 30 minutes |
| Captions: | Wendi Bacon |
| Created: | 15 February 2021 |
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Demo Video
| Description: | 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! |
| Length: | 30 minutes |
| Captions: | Wendi Bacon |
| Created: | 15 February 2021 |
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Tutorial Video
| Description: | Bulk RNA-seq data contains a mixture of transcript signatures from several types of cells. We wish to deconvolve this mixture to obtain estimates of the proportions of cell types within the bulk sample. To do this, we can use single cell RNA-seq data as a reference for estimating the cell type proportions within the bulk data. In this tutorial, we will use bulk and single-cell RNA-seq data, including matrices of similar tissues from different sources, to illustrate how to infer cell type abundances from bulk RNA-seq. |
| Length: | 20 minutes |
| Captions: | Mehmet Tekman, Wendi Bacon |
| Created: | 8 March 2021 |
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