ABSTRACT
The ongoing SARS-CoV-2 pandemic, which emerged in December 2019, revolutionized genomic surveillance, leading to new means of tracking viral spread and monitoring genetic changes in their genomes over time. One of the key sequencing methods used during the pandemic is based on massively parallel short read sequencing based on Illumina technology. In this work, we present a highly scalable and easily deployable computational pipeline for the analysis of Illumina sequencing data, which is used in Slovak SARS-CoV-2 genomic surveillance efforts. We discuss several issues that arose during the pipeline design, and which could both provide useful insight into the analysis processes and serve as a guideline for optimized future outbreak surveillance projects. Copyright © 2021 for this paper by its authors.
ABSTRACT
Estimation of proportions of SARS-CoV-2 genome variants (e.g. variant B.1.1.7 originating from Britain, variant B.1.351 originating from South-Africa) in a population is currently done by sequencing individual samples, which demands individual laboratory processing of each sample. This labor can be significantly reduced by mixing several samples together and processing them in one batch. Our project aims to estimate the proportion of samples with given variants from such mixtures using probabilistic modeling. Copyright © 2021 for this paper by its authors.
ABSTRACT
We present an unofficial SARS-CoV-2 genomic surveillance report from Slovakia based on approximately 3500 samples sequenced between March 2020 and May 2021. Early samples show multiple independent imports of SARS-CoV-2 from other countries. In Fall 2020, three virus variants (B.1.160, B.1.1.170, B.1.258) dominated as the number of cases increased. In November 2020, B.1.1.7 (alpha) variant was introduced in Slovakia and quickly became the most prevalent variant in the country (> 75% of new cases by early February 2021 and > 95% in mid-March). Copyright © 2021 for this paper by its authors.
ABSTRACT
One of the advantages of nanopore sequencing is its ability to provide data in real time, which allows monitoring, early stopping, and fast identification of mutations in sequenced material. Nanopore sequencer measures electrical current induced by the DNA passing through a pore and this signal needs to be translated to a string over the alphabet {A,C,G,T} through a process called base calling. To achieve base calling in real time, the mainstream tools (such as Guppy provided by Oxford Nanopore Technologies) require the support of high-performance GPUs. This is prohibitive in many settings. Here, we evaluate the accuracy of several alternative base callers, which only require use of a desktop CPU or a support of low-cost USB-connected accelerator. While their accuracy is, in general, lower than that of Guppy in a high-accuracy mode using GPUs, we show that these alternative base callers can act as a replacement for monitoring and mutation detection in SARS-CoV-2 sequencing runs, without sacrificing the accuracy of the final result. Copyright © 2021 for this paper by its authors.
ABSTRACT
In this study, we ascertain the associations between BCG vaccination policies and the disease progression in the initial phases of COVID-19 pandemics through analysis of various time-adjusted indicators either directly extracted from the incidence and death reports, or estimated as parameters of disease progression models. We observe weak correlation between BCG vaccination status and indicators related to disease reproduction characteristics. We did not find any associations with case fatality rates (CFR), but the differences in CFR estimates were likely dominated by differences in testing and case reporting between countries. Copyright © 2021 for this paper by its authors.