In the context of a global and collaborative setting in which multiple laboratories are involved in SARS-CoV-2 surveillance and sequencing, it is critical to effectively integrate and standardise the results produced by different teams. This document describes the challenge of integrating different sources of raw genomic data and proposes a series of recommendations as to how to minimise biases and problems when analysing datasets combining raw data drawn from heterogeneous sources.

Datasets can be highly heterogenous in nature and their bioinformatics analysis involves numerous time-consuming processing steps to assemble them within a single full analysis pipeline. In this “bioinformatics pipeline”, we provide a ‘best-practice’ case study example for analysing heterogenous samples. Detailed annotation of all the steps as well as the scripts needed to reproduce the analysis are available on the Github platform at https://github.com/END-VOC/WP3_D3.2_SARS-CoV-2_NGS_bioinformatics_pipeline/

This document describes how the consortium will curate, pool, and harmonise anonymised or pseudo-anonymised data collected by various END-VOC consortium partners.

As part of END-VOC efforts, several cohorts collected biological samples that were used during the project study. Several of these samples continue to be available for further research outside of the consortium and beyond the life of the project. This document, Virtual Biobank Directory, gives an overview of the samples available and how to access them.