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!

What else do you want to see? You can submit tool and/or tutorial request on our Single Cell Community Tool Request Spreadsheet.

Requirements

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

• Introduction to Galaxy Analyses

Material

Introduction

Start here if you are new to single cell analysis in Galaxy and want to learn the concepts.

Your first analysis

Start here if you are new to single cell analysis in Galaxy and want to try analysing data.

Case study

These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. The data is messy. The decisions are tough. The interpretation is meaningful. Come here to advance your single cell skills! Note that you get two options for inferring trajectories.

Case study: Reloaded

These tutorials let you follow the same case study analysis of real, messy data but in a programming environment, hosted on Galaxy. So if you want more flexibility, but the same guided steps as the Case Study, you can skip the Case Study and start here instead. Alternatively, try these after completing the Case Study for an easier jump to a coding environment.

End-to-end scRNA-seq Analyses

These tutorials use different methods to analyse scRNA-seq samples

Deconvolution

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

Multiomic Analyses

This section lets you build on mere scRNA analyses into a multiomic future!

Tips, tricks & other hints

These tutorials cover helpful skills for scRNA-seq analysis

Changing data formats & preparing objects

These tutorials cover a range of needs for importing data from different sources, to changing data into different formats to move from one analysis to the other.

Tip: Troubleshooting errors

When something goes wrong in Galaxy, there are a number of things you can do to find out what it was. Error messages can help you figure out whether it was a problem with one of the settings of the tool, or with the input data, or maybe there is a bug in the tool itself and the problem should be reported. Below are the steps you can follow to troubleshoot your Galaxy errors.

1. Expand the red history dataset by clicking on it.
   • Sometimes you can already see an error message here

2. View the error message by clicking on the bug icon galaxy-bug

3. Check the logs. Output (stdout) and error logs (stderr) of the tool are available:
   • Expand the history item
   • Click on the details icon
   • Scroll down to the Job Information section to view the 2 logs:
     • Tool Standard Output
     • Tool Standard Error
   • For more information about specific tool errors, please see the Troubleshooting section
4. Submit a bug report! If you are still unsure what the problem is.
   • Click on the bug icon galaxy-bug
   • Write down any information you think might help solve the problem
     • See this FAQ on how to write good bug reports
   • Click galaxy-bug Report button
5. Ask for help!
   • Where?
     • In the Single cell user community
     • In the GTN Matrix Channel
     • In the Galaxy Matrix Channel
     • Browse the Galaxy Help Forum to see if others have encountered the same problem before (or post your question).
   • When asking for help, it is useful to share a link to your history

Want to explore analysis beyond our tutorials?

Check out workflows shared by users like you!

Want to contribute?

If you want to help us behind the scenes, from testing workflows and tutorials to building tools, join our Galaxy Single Cell Community of Practice!

• point-right Community of Practice
• feedback Matrix Chat Forum
• email Mailing List

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.

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Editorial Board

This material is reviewed by our Editorial Board:

Wendi Bacon

Mehmet Tekman

Pavankumar Videm

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:

Mehmet Tekman

Beatriz Serrano-Solano

Marisa Loach

Nicola Soranzo

Graham Etherington

Cristóbal Gallardo

Morgan Howells

Helena Rasche

Bérénice Batut

Camila Goclowski

Saskia Hiltemann

Alex Ostrovsky

Hans-Rudolf Hotz

Daniel Blankenberg

Pablo Moreno

Graeme Tyson

Wolfgang Maier

Julia Jakiela

Jonathan Manning

Wendi Bacon

Pavankumar Videm

Anika Erxleben

Funders

This material was funded by:

EPSRC/OU

EOSC-Life

ELIXIR Fair Data

References

• Tekman, Mehmet and Batut, Bérénice; Ostrovsky, Alexander; Antoniewski, Christophe; Clements, Dave; Ramirez, Fidel; Etherington, Graham J; Hotz, Hans-Rudolf; Scholtalbers, Jelle; Manning, Jonathan R; Bellenger, Lea; Doyle, Maria A; Heydarian, Mohammad; Huang, Ni; Soranzo, Nicola; Moreno, Pablo; Mautner, Stefan; Papatheodorou, Irene; Nekrutenko, Anton; Taylor, James; Blankenberg, Daniel; Backofen, Rolf; Grüning, Björn;: A single-cell RNA-sequencing training and analysis suite using the Galaxy framework
• Pablo Moreno, Ni Huang, Jonathan R Manning, Suhaib Mohammed, Andrey Solovyev, Krzysztof Polanski, Wendi Bacon, Ruben Chazarra, Carlos Talavera-López, Maria A Doyle, Guilhem Marnier, Björn Grüning, Helena Rasche, Nancy George, Silvie Korena Fexova, Mohamed Alibi, Zhichao Miao, Yasset Perez-Riverol, Maximilian Haeussler, Alvis Brazma, Sarah Teichmann, Kerstin B Meyer, Irene Papatheodorou;: User-friendly, scalable tools and workflows for single-cell RNA-seq analysis