Genome MedicineBioinformaticsPeer-reviewed journal article
INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance
Vítor BorgesiD, Miguel M. PinheiroiD, Pedro PechirraiD, Raquel GuiomariD, João Paulo GomesiD
Abstract
A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Here, we launch INSaFLU (\"INSide the FLU\"), which, to the best of our knowledge, is the first influenza-specific bioinformatics free web-based suite that deals with primary data (reads) towards the automatic generation of the output data that are actually the core first-line \"genetic requests\" for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and highly flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus completely cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis. This platform additionally flags samples as \"putative mixed infections\" if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional \"consensus-based\" influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants, but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. In summary, INSaFLU supplies public health laboratories and influenza researchers with an open \"one size fits all\" framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.\n\nINSaFLU can be accessed through https://insaflu.insa.pt (see homepage view in Figure 1).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC=\"FIGDIR/small/253161_fig1.gif\" ALT=\"Figure 1\">\nView larger version (26K):\norg.highwire.dtl.DTLVardef@1111419org.highwire.dtl.DTLVardef@3e99c2org.highwire.dtl.DTLVardef@1e0a953org.highwire.dtl.DTLVardef@8c9ea6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO INSaFLU homepage\n\nC_FIG
- organism: virus
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: phylogenetics / evolution
- research focus: database / resource
- research focus: benchmarking
- approach: experimental assay
- Citations
- 80
- FWCI
- 4.29
- Field percentile
- top 5%
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