Training in single-cell sequencing analysis for the Human Cell Atlas

Lead Research Organisation: European Bioinformatics Institute
Department Name: Training

Abstract

Single cell sequencing provides researchers with the opportunity to study single cells in great detail. By looking at the expression of RNA within individual cells, scientists can determine more detail about what that cell is doing, any changes to the cell etc and then compare these results across cells of the same type. This is particularly important for pulling out rare cell types and gives researchers a much better picture of the differences between cells within eg a tissue or organ. Single cell sequencing has the potential to provide impact in many areas of biomedical science, and by creating a further group of well-trained scientists in this are, we can hope to push this potential further.

The aim of this project is to provide suitable training to a large group of researchers working with single-cell sequencing which will enable them to make more of the studies they are undertaking. scRNA-sequencing requires specialist analysis, and the data created during such experiments needs to be recorded and managed in a way that makes it easily usable by others. Enabling researchers to analyse their own data will help them further their research, and by submitting the data they generate to public resources, they will further help others to undertake more research.

Technical Summary

We have identified a number of key elements of research support provision which can be delivered through training to enable greater impact of the HCA within the UK research community and beyond.
- Good data management practices and high quality data submission to the HCA
- Single-cell RNA sequence analysis
- Biological interpretation of analysis outputs

We will therefore be delivering both face to face and online training to researchers who are using scRNA-Sequencing in their studies who require support in developing sound data management practices when generating such data, upskilling them in the analysis of this data and enabling its submission, in high quality format, to the HCA for access by others in the wider biological / biomedical research communities. This will maximise the value of data submitted by UK researchers to the global research community.

Planned Impact

Through the training to be developed and delivered through the course of this research we believe there will be direct impact in researchers both in the UK and beyond who are working with scRNA-Sequence and analysing such data. The upskilling of UK based researchers to enable them to both generate and analyse high-quality scRNA-sequence data has the potential to generate significant economic and societal benefit. Data generated via this technique has the potential to transform basic biological / biomedical knowledge, and through the translation of such knowledge into clinical settings can lead to the generation of new technologies etc based on such findings. These can have both economic impact in terms of new technology development and application; and societal impact due to their use in clinical settings where their use could transform patient management.

The impact of such training will not be one-way however, as researchers in the field will be brought in to define the final scope of the training delivered, ensuring it enables them to meet the challenges they face and gain the skills required to overcome these.

Further impact is envisaged through other researchers utilising the data deposited into the HCA, with additional economic and societal impacts due to their analysis of this publicly accessible data and the potential stimulation of further research which in turn will generate additional data.

Publications

10 25 50
 
Title Generating a cell matrix using Alevin - Galaxy workflow and associated tutorial 
Description This tutorial presents a reusable Galaxy workflow covering the initial stages of single cell RNA-Seq analysis along with example histories, published within the Galaxy training network environment. The reusable workflows presented here are based on a production pipeline from EMBL-EBI's single cell expression atlas (SCXA). This pipeline is used for SCXA data analysis, wherein they have wrapped various code into user-friendly tools to run in a browser-based Galaxy interface. The impact of these tools can extend far beyond the SCXA resource, however, because the open-access Galaxy project itself allows people with no coding ability to analyse their data with the user-friendly tools. 
Type Of Material Data analysis technique 
Year Produced 2021 
Provided To Others? Yes  
Impact By creating sharable workflows, example histories of analysis, and adapting, updating or improving these tools, we have created this tutorial to allow scientists from across the world access to the same analytical capabilities as the EBI's single cell team. It is used initially to teach the basic steps of single cell analysis, but can additionally be used as a start point for researchers to analyse their own data. These tutorials are used globally, both by interested scientists as well as within the EMBL-EBI courses delivered under this award. 
URL https://usegalaxy.org.au/training-material//topics/transcriptomics/tutorials/droplet-quantification-...