Single Cell

Training material and practicals for all kinds of single cell analysis (particularly scRNA-seq!). When you generate your lovely gene lists for your cells, consider checking out our Transcriptomics tutorials for further network analysis!

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides (slides) and tutorial (tutorial) buttons below.

Requirements

Before diving into this topic, we recommend you to have a look at:

Material

Introduction

Start here if you are new to single cell analysis in Galaxy

Lesson Slides Hands-on Recordings Input dataset Workflows
An introduction to scRNA-seq data analysis
Understanding Barcodes
Plates, Batches, and Barcodes

Case study

These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. Note you have two different options for trajectory analysis - Scanpy in Python/Jupyter Notebook, or Monocle3 in the Galaxy user interface.

Lesson Slides Hands-on Recordings Input dataset Workflows
Generating a single cell matrix using Alevin
Combining datasets after pre-processing
Filter, Plot and Explore Single-cell RNA-seq Data
Inferring Trajectories using Scanpy (Python)
Inferring trajectories using Monocle3
Inferring Trajectories using Monocle3 (R)

Deconvolution

These tutorials infer cell compositions from bulk RNA-seq data using a scRNA-seq reference

Lesson Slides Hands-on Recordings Input dataset Workflows
Bulk RNA Deconvolution with MuSiC
Creating the single-cell RNA-seq reference dataset for deconvolution
Creating the bulk RNA-seq dataset for deconvolution
Comparing inferred cell compositions using MuSiC deconvolution

End-to-end Analyses

These tutorials use different methods to analyse scRNA-seq samples

Lesson Slides Hands-on Recordings Input dataset Workflows
Pre-processing of Single-Cell RNA Data
Downstream Single-cell RNA analysis with RaceID
Pre-processing of 10X Single-Cell ATAC-seq Datasets
Pre-processing of 10X Single-Cell RNA Datasets
Clustering 3K PBMCs with Scanpy
Analysis of plant scRNA-Seq Data with Scanpy

Tips, tricks & other hints

These tutorials cover helpful skills for scRNA-seq analysis

Lesson Slides Hands-on Recordings Input dataset Workflows
Single-cell quality control with scater
Removing the effects of the cell cycle

Galaxy instances

You can use a public Galaxy instance which has been tested for the availability of the used tools. They are listed along with the tutorials above.

Frequently Asked Questions

Common questions regarding this topic have been collected on a dedicated FAQ page . Common questions related to specific tutorials can be accessed from the tutorials themselves.

Maintainers

This material is maintained by:

orcid logoAvatarWendi BaconAvatarMehmet Tekman

For any question related to this topic and the content, you can contact them or visit our Gitter channel.

Contributors

This material was contributed to by:

orcid logoAvatarGraeme Tysonorcid logoAvatarBeatriz Serrano-SolanoAvatarEOSC-Lifeorcid logoAvatarWolfgang Maierorcid logoAvatarBérénice Batutorcid logoAvatarAnika Erxlebenorcid logoAvatarGraham Etheringtonorcid logoAvatarWendi Baconorcid logoAvatarPavankumar VidemAvatarJonathan Manningorcid logoAvatarCristóbal Gallardoorcid logoAvatarHans-Rudolf HotzAvatarMehmet Tekmanorcid logoAvatarDaniel Blankenbergorcid logoAvatarNicola SoranzoAvatarEPSRC Training Grant DTP 2020-2021 Open Universityorcid logoAvatarAlex Ostrovskyorcid logoAvatarHelena RascheAvatarJulia Jakielaorcid logoAvatarMarisa Loach

References