V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation (preprint)

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

How much should we sequence? An analysis of the Swiss SARS- CoV-2 surveillance effort (preprint)

Background During the SARS-CoV-2 pandemic, many countries directed substantial resources towards genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. Aim We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic dataset from Switzerland, comprising more than 143k sequences. Methods We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. Results The impact of downsampling on VOC detection is disparate for the three VOC lineages , but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. Conclusion A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage dependent - something that is unknown at the time of sequencing - and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.