Research Environment Training Session: Working with the new aggregate VCFs – AggV3

Genomics England provide multi-sample VCFs, aggregating together variant calls for participants from the 100,000 Genomes project, NHS Genomic Medicine Service and Covid-19 data. This allows you to query genomic loci and annotation in all participants using tools such as bcftools. A new version of the aggregate, known as AggV3, will be released in 2026 based on genomes realigned using Dragen 3.7.8 and made available only in CloudOS. 

This training session will introduce you to working with AggV3 using interactive sessions in the CloudOS platform. We will show you how to launch interactive sessions, including the cloud instance options available, and how to run tools in the terminal. We will use bedtools to identify the correct VCF files to work with, and bcftools to query a genomic locus for participant genotypes. To allow you to combine genotype queries in CloudOS with phenotype queries using other tools, we will look at taking data in and out of CloudOS. 

You are only allowed to attend this session if you are eligible for data access. This means that you are a Research Network member that has met the necessary verification checks and passed our Information Governance training course. If you do not meet this criterion by 9th March 2026 you will be unregistered for this session. 

Timetable

13.30 Introduction and admin   

13.35 How were the AggV3 multisample VCFs created? 

13.50 Interactive sessions in CloudOS 

14.10 Querying AggV3 in the terminal 

14.30 Taking data in and out of CloudOS 

14.45 Getting help and questions 

Learning objectives

After this training you will 

• Have a better understanding of the dataset and what is included
• Know how to query AggV3 in a CloudOS interactive session
• Know how to combine genotype queries of AggV3 with phenotype analysis 

Target audience

This training is aimed at researchers: 

• Working with the Genomics England Research Environment
• Familiar with the command line and standard bioinformatics tools