Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

Goya, Stephanie; Sosa, Ezequiel; NabaesJodar, Mercedes; Torres, Carolina; König, Guido; Acuña, Dolores; Ceballos, Santiago; Distéfano, Ana Julia; Dopazo, Hernán; Santos, María Dus; Fass, Mónica; Porto, Darío Fernández Do; Fernández, A.; Gallego, Fernando Martín; Gismondi, María Inés; Gramundi, Ivan; Lusso, Silvina; Martí, Marcelo A.; Mazzeo, M; Mistchenko, Alicia; Marianne, G Muñoz Hidalgo; Natale, Mónica; Nardi, Cristina Fernanda; Ousset, Julia; Peralta, Andrea; Pintos, Carolina; Puebla, Andrea Fabiana; Pianciola, Luis; Rivarola, Máximo Lisandro; Turjanski, Adrián; Valinotto, Laura; Vera, Pablo Alfredo; Zaiat, Jonathan; Zubrycki, Jeremías; Aulicino, Paula; Viegas, Mariana

doi:10.1016/j.virusres.2022.199035

Cited by 2 publications

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While there are pipelines that integrate reproducible workflows to analyze genomic diversity between patients [14,15], there is a lack of easily deployable, accessible, and integrated workflows for analyzing and reporting the evolutionary trajectories of SARS-CoV-2 chronic infections. Current pipelines for processing serially-sampled sequencing data that take into account the particularities of intra-host samples are restricted to certain analyses, such as detecting mixed viral populations, or identifying chronic infections but using only consensus sequences [12,[16][17][18][19]. For this reason, carrying out this type of studies through public databases is a difficult task especially without further clinical information.…”

Section: Introductionmentioning

confidence: 99%

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Álvarez-Herrera,

Sevilla,

Ruiz-Rodriguez

et al. 2023

Preprint

View full text Add to dashboard Cite

Viral mutations within patients nurture the adaptive potential of SARS-CoV-2 during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein we describe VIPERA (Viral Intra-Patient Evolution Reporting and Analysis), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. It has been validated using positive and negative control datasets and successfully applied to a novel case, contributing to easy and automatic analysis of intra-patient SARS-CoV-2 sequences.

show abstract

Section: Introductionmentioning

confidence: 99%

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Álvarez-Herrera,

Sevilla,

Ruiz-Rodriguez

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Álvarez-Herrera,

Sevilla,

Ruiz-Rodriguez

et al. 2024

Virus Evolution

View full text Add to dashboard Cite

Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.

show abstract

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

Cited by 2 publications

References 40 publications

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Contact Info

Product

Resources

About