PathoSeq-QC :A bioinformatic pipeline that allows robust analysis of next generation sequencing raw data associated to viruses

High-throughput genomic sequencing emerged as a key technology in combating global health threats such as the COVID-19 pandemic. Integrated with Bioinformatics and epidemiological data, it provides crucial insights into pathogenic threats, their evolutionary dynamics, and facilitates the monitoring of pathogen spread. Moreover, it aids in evaluating the efficacy of policy interventions. From a policymaking perspective, standardized and harmonized quality procedures are essential prior to drawing any analysis and conclusions, particularly during pandemics where timely and accurate results are imperative for effective decision-making. Without such measures, there exists a significant risk of misinterpretation of data. For instance, erroneous identification of nucleotide mutations in genomic analyses may lead to the mistaken assumption of the emergence of novel lineages, potentially influencing policy decisions regarding countermeasures. Additionally, the absence of shared protocols and workflows between different institutions might lead to different conclusions even when starting from the same input data. Based on the previous, we introduce PathoSeq-QC, a bioinformatics "decision-tree" workflow designed to ensure that conclusions drawn from genomic data are based on robust and high-quality inputs. This versatile tool not only evaluates sample and sequencing data quality but also robustly identifies variants and assigns viral lineages. While initially tailored for SARS-CoV-2, PathoSeq-QC can be adapted to various viral threats. PathoSeq-QC is anticipated to enhance the resilience of pathogen surveillance protocols by applying stringent quality criteria, thereby mitigating the risk of erroneous conclusions that could impact both the work of researches and the decision-making processes.