• COVID-19
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Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic

This repository include python code scripts used in "A machine learning approach to predict self-protecting behaviors during the early wave of the COVID-19 pandemic"

[2.6.0] - 2023-03-23 Credits Special thanks to the following for their code contributions to the release: Friederike Hanssen Hugo Tavares James Fellows Yates Jessica Wu Matthew Wells Maxime Garcia Phil Ewels Sara Monzón Thank you to everyone else that has contributed by reporting bugs, enhancements or in any other way, shape or form. Enhancements & fixes [#297] - Add tube map for pipeline [#316] - Variant calling isn't run when using --skip_asciigenome with metagenomic data [#317] - ivar_variants_to_vcf: Ignore lines without annotation in ivar tsv file [#320] - Pipeline fails at email step: Failed to invoke workflow.onComplete event handler [#321] - ivar_variants_to_vcf script: Duplicated positions in tsv file due to overlapping annotations [#334] - Longshot thread 'main' panicked at 'assertion failed: p <= 0.0' error [#341] - artic/minion and artic/guppyplex: Update module version 1.2.2 -> 1.2.3 [#348] - Document full parameters of iVar consensus [#349] - ERROR in Script plasmidID [#356] - Add NEB SARS-CoV-2 primers [#368] - Incorrect depth from ivar variants reported in variants long table Updated pipeline template to nf-core/tools 2.7.2 Add tower.yml for Report rendering in Nextflow Tower Use --skip_plasmidid by default Parameters Old parameter New parameter --tracedir NB: Parameter has been updated if both old and new parameter information is present. NB: Parameter has been added if just the new parameter information is present. NB: Parameter has been removed if new parameter information isn't present. Software dependencies Note, since the pipeline is now using Nextflow DSL2, each process will be run with its own Biocontainer. This means that on occasion it is entirely possible for the pipeline to be using different versions of the same tool. However, the overall software dependency changes compared to the last release have been listed below for reference. Dependency Old version New version artic 1.2.2 1.2.3 bcftools 1.51.1 1.16 blast 2.12.0 2.13.0 cutadapt 3.5 4.2 ivar 1.3.1 1.4 multiqc 1.13a 1.14 nanoplot 1.40.0 1.41.0 nextclade 2.2.0 2.12.0 pangolin 4.1.1 4.2 picard 2.27.4 3.0.0 samtools 1.15.1 1.16.1 spades 3.15.4 3.15.5 NB: Dependency has been updated if both old and new version information is present. NB: Dependency has been added if just the new version information is present. NB: Dependency has been removed if new version information isn't present.

Background The clinical course of COVID-19 patients ranges from asymptomatic infection, via mild and moderate illness, to severe disease and even fatal outcome. Biomarkers which enable an early prediction of the severity of COVID-19 progression, would be enormously beneficial to guide patient care and early intervention prior to hospitalization. Methods Here we describe the identification of plasma protein biomarkers using an antibody microarray-based approach in order to predict a severe cause of a COVID-19 disease already in an early phase of SARS-CoV-2 infection. To this end, plasma samples from two independent cohorts were analyzed by antibody microarrays targeting up to 998 different proteins. Results In total, we identified 11 promising protein biomarker candidates to predict disease severity during an early phase of COVID-19 infection coherently in both analyzed cohorts. A set of four (S100A8/A9, TSP1, FINC, IFNL1), and two sets of three proteins (S100A8/A9, TSP1, ERBB2 and S100A8/A9, TSP1, IFNL1) were selected using machine learning to identify a multimarker panel with sufficient accuracy for the implementation in a prognostic test. Conclusions Using these biomarkers, patients at high risk of developing a severe or critical disease course may be selected for treatment with specialized therapeutic options such as neutralizing antibodies or antivirals. Early therapy through early stratification may not only have a positive impact on the outcome of individual COVID-19 patients but could additionally prevent hospitals from being overwhelmed. This code was used for the machine learning subsection of the Materials & Methods section.

vdb: 'sequence' command added to provide the reconstructed sequence for a consensus pattern or for an isolate. Lineage relationships are correct and consistent between VDB.sublineagesOfLineage() and VDB.parentLineageFor(). Lineage names are standardized when necessary. Lineage name with wildcard includes sublineages even when excludeSublineages is set. Added command aliases 'parent' and 'info' for characteristics of lineage command. Mutation list added to cluster subscript info list. Improved lineage relationships for recombinant lineages. GenBank accession numbers accepted for tree bracket commands. Command 'most <tree name> <cluster name>' added to tree version for finding nodes with highest leaf counts. 'checkGlyco', 'checkLineages', and 'assign weights' commands added for embedded version. Expr.patternFromExpr() function changed to optional return type. Fixed potential bug in numberFromAccString(). Added 'root' as an alias for blank lineage name. Added 'A' and 'B' as sublineages of root lineage. Wildcard character defined in constants. Fixed bug in protein mutation search in nucleotide mode. Restored codon-specific counts for a protein mutation in nucleotide mode. infoForPosition() output is now in table form. infoForPosition() command (i.e., a position number) can now accept a defined cluster name as a second argument. Added sublineages 'direct' option to limit output to direct sublineages. Added lineage alias info to characteristicsOfLineage() output. Fixed bug in isPattern() function. Improved automatic insertion of lineage keyword for alias names in processLine() function. Tree node bracket command allows subtree to be assigned using a node id (previously only lineage names could be used). Tree variable equality testing added.

Quick start with Docker: Download and expand the zip cd docker ./docker-run.sh The latter will launch a small/demo dataset, see the documentation for using real dataset. See the revision history for a list of new features and changes.

Package version used in "Multi-level proteomics reveals host-perturbation strategies of SARS-CoV-2 and SARS-CoV" Stukalov et al. (2020)

updated the scripts related to the mpxv project. Full Changelog: https://github.com/innatelab/analysis_utils_jl/compare/v1.0.0...v1.1.0_mpxv

Research with the National COVID Cohort Collaborative (N3C) If you use this software, please cite it as below

Major release tweaking the JSON output, fixes the returning of identifiers in the/xrefBatch/$DataSource call, fixes a few error messages for bad input, and includes many more tests and some further code clean up. Everyone is encouraged to upgrade to this version. Full Changelog: https://github.com/bridgedb/BridgeDbWebservice/compare/2.1.2...2.1.3 If you use this software, please cite it as below.