From a9cc39862907424f71b8dff91548b257cf8a7788 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Miguel=20=C3=81lvarez=20Herrera?= Date: Thu, 21 Mar 2024 12:39:03 +0100 Subject: [PATCH] Update publication --- CITATION.cff | 30 ++++++++++++++++-------------- README.md | 25 +++++++++++++++---------- 2 files changed, 31 insertions(+), 24 deletions(-) diff --git a/CITATION.cff b/CITATION.cff index f7d5410..191194b 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -88,30 +88,32 @@ authors: Unit “Infection and Public Health”, Paterna, Spain identifiers: - type: doi - value: 10.1101/2023.10.24.561010 - description: Preprint + value: 10.1093/ve/veae018 + description: Journal article - type: doi value: 10.20350/digitalCSIC/15648 description: >- Case study data: SARS-CoV-2 mapped reads and consensus genomes of an intra-patient serially sampled infection repository-code: 'https://github.com/PathoGenOmics-Lab/VIPERA' -url: 'https://doi.org/10.1101/2023.10.24.561010' +url: 'https://doi.org/10.1093/ve/veae018' abstract: >- 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 intrapatient 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 + 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, thus - enabling an easy and automatic analysis of intra-patient - SARS-CoV-2 sequences. + 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. keywords: - SARS-CoV-2 - Intra-host viral evolution @@ -119,4 +121,4 @@ keywords: - Bioinformatics - Snakemake license: GPL-3.0 -version: 1.0.0 +version: 1.2.0 diff --git a/README.md b/README.md index 36c74ea..a112593 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@

[![PGO badge](https://img.shields.io/badge/PathoGenOmics-Lab-yellow.svg)](https://pathogenomics.github.io/) -[![DOI:10.1101/2023.10.24.561010](https://img.shields.io/badge/DOI-10.1101/2023.10.24.561010-blue.svg)](https://doi.org/10.1101/2023.10.24.561010) +[![DOI](https://img.shields.io/badge/Virus_Evolution-10.1093/ve/veae018-387088.svg)](https://doi.org/10.1093/ve/veae018) [![Release](https://img.shields.io/github/v/release/PathoGenOmics-Lab/VIPERA)](https://github.com/PathoGenOmics-Lab/VIPERA/releases) [![Snakemake](https://img.shields.io/badge/Snakemake-≥7.19-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io) ![Install workflow](https://github.com/PathoGenOmics-Lab/VIPERA/actions/workflows/install.yml/badge.svg) @@ -24,7 +24,7 @@ configuring [the inputs and outputs](config/README.md#inputs-and-outputs) and snakemake --use-conda -c4 # runs VIPERA on 4 cores ``` -We provide a simple script that downloads the [data](https://doi.org/10.20350/digitalCSIC/15648) from [our study](https://doi.org/10.1101/2023.10.24.561010) +We provide a simple script that downloads the [data](https://doi.org/10.20350/digitalCSIC/15648) from [our study](https://doi.org/10.1093/ve/veae018) and performs the analysis in a single step: ```shell @@ -49,18 +49,23 @@ Please refer to the [full workflow documentation](config/README.md) for detailed ## Citation -Álvarez-Herrera M. & Sevilla, J., Ruiz-Rodriguez, P., Vergara, A., Vila, J., Cano-Jiménez, P., González-Candelas, F., Comas, I., & Coscolla, M. (2023). VIPERA: Viral Intra-Patient Evolution Reporting and Analysis. bioRxiv. https://doi.org/10.1101/2023.10.24.561010 +> Álvarez-Herrera, M. & Sevilla, J., Ruiz-Rodriguez, P., Vergara, A., Vila, J., Cano-Jiménez, P., González-Candelas, F., Comas, I., & Coscollá, M. (2024). VIPERA: Viral Intra-Patient Evolution Reporting and Analysis. Virus Evolution, 10(1), veae018. https://doi.org/10.1093/ve/veae018 ```bibtex -@misc{AHS_VIPERA_2023, +@article{ahs2024, title = {{VIPERA}: {Viral} {Intra}-{Patient} {Evolution} {Reporting} and {Analysis}}, + volume = {10}, + issn = {2057-1577}, shorttitle = {{VIPERA}}, - author = {Álvarez-Herrera$^*$, Miguel and Sevilla$^*$, Jordi and Ruiz-Rodriguez, Paula and Vergara, Andrea and Vila, Jordi and Cano-Jiménez, Pablo and González-Candelas, Fernando and Comas, Iñaki and Coscolla, Mireia}, - url = {https://www.biorxiv.org/content/10.1101/2023.10.24.561010}, - doi = {10.1101/2023.10.24.561010}, - language = {en}, - urldate = {2023-10-25}, - publisher = {bioRxiv}, + url = {https://doi.org/10.1093/ve/veae018}, + doi = {10.1093/ve/veae018}, + abstract = {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.}, + number = {1}, + journal = {Virus Evolution}, + author = {Álvarez-Herrera$^*$, Miguel and Sevilla$^*$, Jordi and Ruiz-Rodriguez, Paula and Vergara, Andrea and Vila, Jordi and Cano-Jiménez, Pablo and González-Candelas, Fernando and Comas, Iñaki and Coscollá, Mireia}, + month = jan, + year = {2024}, + pages = {veae018}, note = {$^*$ indicates equal contribution} } ```