Research Environment Training Session: Working with Python in the Research Environment

Python is a powerful programming language with numerous libraries for biological data analysis and visualisation. Within the Genomics England Research Environment, you have access to many versions of Python and associated packages, along with Jupyter Lab for interactive analysis. There are a number of pre-built conda environments you can use, and you can build your own. The High Performance Cluster allows you to run analyses with significant compute.

In this training session, you will learn how to work in Jupyter in the Research Environment, to run your python scripts on the HPC, which may be different to how you are used to working outside the Research Environment. You will learn how to see details and contents of pre-built conda environments, and learn how to build your own using the limited channels that have been enabled in the Research Environment. You will also learn how to access clinical data with python.

You are only allowed to attend this session if you are eligible for data access. This means that you are a Research Network or Discovery Forum member that has met the necessary verification checks and passed our Information Governance training course. If you do not meet this criterion by 7th April 2025 you will be unregistered for this session.

Timetable

13.30 Welcome and introduction

13.35 Pre-built conda environments in the Research Environment

13.45 Create conda environments in the Research Environment

13.55 Working with Jupyter on the HPC

14.15 Query clinical data with Python

14.45 Getting help and questions

Learning objectives

After this training you will know:

• How to use Jupyter notebooks on the High Performance Cluster
• How to use pre-built conda environments in the Research Environment and build your own
• How to query Genomics England clinical data with Python

Target audience

This training is aimed at researchers who:

• Are working in the Genomics England Research Environment
• Can programme in Python