Course Description:

Spatial transcriptomics is transforming how we understand tissue biology, but many teams still work in isolation, reinventing the same pipelines and solving the same problems in parallel. To address these specific challenges, SpatiaLondon was founded by five London institutions (KCL, UCL, Imperial, QMUL, and the Francis Crick Institute) with fundings from Francis Crick Institute and DisCouRSE+, to share practice, align standards, and co-create the open tools and training the field needs. SpatiaLondon is open to researchers, bioinformaticians, and platform engineers across the UK interested in addressing the challenges of spatial biology. 

The SpatiaLondon Workshop series is designed to address key challenges in spatial biology data, including data formats, QA/QC, spatial imaging problems, cell segmentation models, cell annotation models, batch effect correction methods, neighbourhood analysis methods and downstream analysis. SpatiaLondon workshop series also covers application and implementation of AI models in spatial biology. 

Please click on the "More Info" tab for further information about the course and sessions that are available.

Individual Sessions are £100. Save by buying a bundle of all sessions for £500!

Registration for each session will close four days in advance. Bundles will be available until before Session 2.

Please select the attendee category below that is applicable to you. You will then need to select which session/s you wish to attend on the next page. 

Any bookings where payment hasn't been taken will be cancelled.

6th October 2026 (10:00 - 13:00)

Completion of the online module Unix and IT Infrastructure for Data Analysis is required before attending this in-person workshop. 

Learn the Unix skills that underpin modern bioinformatics. In this module, you'll discover how command-line tools transform raw sequencing data into meaningful biological insights and gain an understanding of the IT infrastructure that supports reproducible bioinformatics workflows. These core skills provide the foundation for many of the analyses covered in subsequent workshops. 

This is an in-person workshop. Completion of the associated online module (https://learninghub.kingshealthpartners.org/course/unix) is mandatory prior to attendance.  

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

Completion of the online module Basic R With Data Carpentry is required before attending this in-person workshop.

R is one of the most used programming languages in Data Science to perform data analysis, used to visualize the data, to apply statistics and for machine learning analyses. This course is designed for participants with no programming experience and is the most beginner-friendly course within Innovation Scholars. We will be using example questions related to health research to learn how to write ad-hoc codes to manipulate and visualize data using R packages designed for Big Data analyses. 

This course is for you if: 

• You are a complete/near complete beginner to programming 
• Work in health-related sector as either clinical, administrative or academic staff - for example as a nurse, health administrator, consultant, biomedical researcher, etc. You require flexible learning format 
• You need to start using more data for your current or future role 
• You want to be able to perform basic tasks in R, such as making plots and sorting through tables, based on health-data without getting too deep into the theory of coding 

This is an in-person workshop (10:00 - 13:00).  

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk 

Completion of the online module Statistics with R is required before attending this in-person workshop.

This course will provide practical examples of how to perform statistical tests using the R software environment. We will explore the most widely used statistical tests and will explain the basic concept behind applying a stats test in R so that participants will be able to apply their knowledge to other tests not covered in this course. A basic knowledge of the statistical tests and a basic knowledge of R and Rstudio are essential. 

This course is for you if: 

• You need to apply statistical tests on large datasets in your current or future role You have a basic or higher level of programming using R and Rstudio 
• You have a basic or higher understanding of statistics 
• You work in health-related sector as either clinical, administrative or academic staff - for example as a nurse, health administrator, consultant, biomedical researcher, etc. 
• You require flexible learning format 

This is an in-person workshop. Completion of the associated online module (https://learninghub.kingshealthpartners.org/course/statistics-with-r) is mandatory prior to attendance.  

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk 

12th January 2027 - 10am - 1pm

Completion of the online Introduction to High-Performance Computing (HPC) is required before attending this in-person workshop 

Take your HPC skills further with a practical, hands-on workshop focused on high-performance computing concepts to real-world biomedical research workflows. Building on the material covered in the online course (https://learninghub.kingshealthpartners.org/course/introduction-to-hpc), this session provides the opportunity to gain practical experience using an HPC system, manage data efficiently, and develop confidence working in a shared computational environment. 

During the workshop, you will work through guided exercises using an HPC cluster, practising key tasks including navigating the Linux command line, managing files and directories, transferring data, writing and running scripts, and submitting and monitoring jobs. You will also have the opportunity to ask questions and receive guidance from the instructor to reinforce your understanding of HPC workflows. 

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

Following the recent announcement that GraphPad Prism will now require individual group subscriptions, the HAB will be offering a new series of hands-on workshops for non-coders.  

These workshops are designed to help researchers at all career levels (PIs included!) to carry out the analyses they would usually perform in GraphPad Prism, this time in R, a powerful open-source alternative.  

We will begin with an introductory module on R basics, followed by a series of topic-focused sessions, helping you to convert your existing Prism-based analyses into the R language. We conclude with a “Bring Your Own Data” workshop where you work with your own datasets with support from our team. 

Each workshop runs for 3 hours (10:00-13:00) and are scheduled every four weeks from January 26 through June 15th. Participants can choose to attend the full series (at a discount!) or select individual modules according to their needs. However, the Basic R module is a prerequisite unless you are already confident with the fundamentals, as we will not re-cover them in later sessions. 

Please click on the "More Info" tab for further information about the course and sessions that are available.

Individual Sessions are £75. Save by buying a bundle of all sessions for £300!

Registration for each session will close two days in advance. Bundles will be available until before Session 2.

If you are selecting individual sessions, you will need to select which session/s you wish to attend on the next page. Any bookings where payment hasn't been taken will be cancelled.

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

4th February 2027 (10:00 - 13:00)

Completion of the online module Using Spreadsheets to Record Data and Metadata is required before attending this in-person workshop.

A good experimental design is the first step for a successful bioinformatics analyses, the second one is to understand how to record and organise data. Most life scientists (at any career stage) store data in spreadsheets, so this is the place that many research projects start and how data are delivered to the bioinformatician. Participants will prepare data for bioinformatics analyses and improve their data organization skills. 

This course is for you if: 

• You are a beginner to using Excel or have experience but would like to use it more effectively 
• You work in health-related sector as either clinical, administrative or academic staff - for example as a nurse, health administrator, consultant, biomedical researcher, etc.
• You have some knowledge of basic statistical terms and would like to apply them in Excel You need to start recording data or using already recorded data for your current or future role
• You require flexible learning format 

Prerequisites:

Completion of the online module Using spreadsheets for recording data and metadata is required prior to attending this workshop. The online module is available here: https://learninghub.kingshealthpartners.org/course/using-spreadsheets

26th February 2027 (10:00 - 13:00)

Completion of the online module online course NGS: RNA-Seq (Part 1) is required before attending this in-person workshop. 

Take your RNA-seq knowledge further with a practical, hands-on workshop focused on data analysis and visualisation. Building on the concepts introduced in the online course (available here: https://learninghub.kingshealthpartners.org/course/next-generation-sequencing-rna-seq ), this in-person follow-up session provides the opportunity to apply your skills through guided exercises, real-world workflows, and expert support.  

During the workshop, you will work through advanced RNA-seq analysis and visualisation tasks, explore practical workflows, ask questions, and receive guidance from the instructor to help consolidate your understanding. 

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

8th April 2027 (10:00 - 13:00)

Completion of the online module Python for Health Research is required before attending this in-person workshop.

Python is a versatile and widely used programming language that has become an essential tool in modern health research. Its simple syntax, extensive libraries, and strong community support make it accessible to researchers with little or no programming experience. In health research, Python is used for data management, statistical analysis, visualization, machine learning, and the integration of large-scale biomedical datasets. As healthcare increasingly relies on data-driven approaches, Python enables researchers to efficiently analyse complex data, automate repetitive tasks, and generate reproducible results. This course provides a practical introduction to Python and its applications in health and biomedical research. 

Take your Python knowledge further with a practical, hands-on workshop that builds on the concepts introduced in the online course (available here: https://learninghub.kingshealthpartners.org/course/introduction-to-python-for-health-research ).  

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

13th April 2027 (10:00 - 17:00)

This full-day, in-person workshop will provide a practical introduction to carrying out common statistical tests in R. Through a combination of short theoretical refreshers, live demonstrations and hands-on exercises, participants will learn how to choose, run, interpret and report statistical tests using real-world, health-related examples. 

We will cover the core principles behind hypothesis testing and give participants the confidence to apply statistical methods to their own datasets. We will explore commonly used tests with an emphasis on understanding when each test is appropriate and how to interpret the output in R. 

This workshop is designed for participants who want a focused, supportive learning environment with live instructor guidance. Participants will build confidence not only in running specific statistical tests, but also in applying the same principles to other analyses in their own work.

Please click on the "More Info" tab for further information.

April 27th 2027 (10:00 - 17:00)

This full-day, hands-on workshop will introduce you to the key steps involved in analysing and visualising Bulk RNA-seq data. You will learn how RNA-seq data are generated, processed and interpreted, with a particular focus on preparing data for downstream analysis and identifying differentially expressed genes. 

By the end of the course, you will have a clearer understanding of what Bulk RNA-seq can tell you, how raw sequencing data are transformed into interpretable results, and how to carry out core analysis steps in R. The workshop is designed to combine explanation with practical exercises, giving you the opportunity to work through an RNA-seq analysis workflow in a focused, supportive, in-person environment. 

Please see the "More Info" tab for further information.

Prerequisites: Working knowledge of the R programming language, knowledge of NGS sequencing and pre-processing such as from our online course.

If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

2nd June 2027 (10:00 - 13:00)

This workshop is a follow-up session to the online Innovations Scholar Workshop. The online workshop *must* be completed before coming to this in-person workshop. Initially we aim to use the data and objects produced from the online workshop to expand on the important aspects of ATAC-seq analysis, discuss decision-making steps along the analysis pipeline.  We will extend the workshop to include the integration of other ‘Omic’ datasets and use different genomic resources to determine potential regulatory networks. Due to time constraints, we are limited to tools that are implemented in R and that run reasonably fast. Where relevant, case studies could be shown and discussed. By the end of the workshop, delegates will be able to independently conduct and critically analyse data from ATAC-seq experiments. 

Please complete the following requirements before attending the workshop: 

• A certificate from the online workshop. 
• RStudio and the installation of all the libraries used in the online workshop. 
• The RDS obtained from the online workshop. 

If you are having any issues, please contact Michelle Simon (michelle.1.simon@kcl.ac.uk) directly. If the event is full or closed for registration, and you would like to register last-minute or be added to a waitlist, please e-mail hab@kcl.ac.uk

We are looking forward to seeing you there! 

Course Description 

This hands-on workshop introduces Git, the industry-standard version control system used to manage, track, and collaborate on research and software projects. Whether you're writing code, analysing data, or developing documents, Git helps you keep a complete history of your work, experiment safely, and collaborate efficiently with others. 

Through a combination of demonstrations and practical exercises, you will learn how to use Git from the command line and work with GitHub to store, share, and collaborate on projects. By the end of the workshop, you will have the confidence to use version control in your own research and computational workflows. 

Topics covered 

• Installing and configuring Git
• Creating and managing Git repositories
• Tracking and committing changes
• Exploring repository history
• Working with remote repositories using GitHub
• Cloning repositories
• Collaborating on shared projects
• Creating, switching, and merging branches 

Who is this course for? 

This workshop is designed for researchers, students, and professionals who are new to version control and would like to incorporate Git into their research or software development workflows. 

Prerequisites 

Participants should: 

• Have a GitHub account before attending the workshop
• Install Git on their computer (installation instructions will be provided)
• Be familiar with the Unix/Linux command line (Bash), including basic commands such as pwd, ls, cd, cat, mkdir, and touch, as the workshop uses the terminal to interact with Git