Change log

This tab includes a list (chronologically ordered) of notable changes in INSaFLU.

2020

May 06, 2020

  • INSaFLU local installation - a Docker version of INSaFLU, which eases the manual installation process, is now available here: https://github.com/INSaFLU/docker
  • Multitasking configurations were changed, considerably speeding up the analyses.
  • A new tab “Settings” was created so that the user can change some software parameters.

All updates are available at both INSaFLU docker version and original free website (https://insaflu.insa.pt/)

March 10, 2020

The following updates have been performed so that INSaFLU can better accommodate genome-based analyses of the novel coronavirus (SARS-CoV-2 / hCoV-19):

  • INSaFLU now performs rapid assignment of Human Betacoronavirus (BetaCoV), including the novel coronavirus (SARS-CoV-2 / hCoV-19). Details about the rationale behind this classification and outputs can be found in https://insaflu.readthedocs.io/en/latest/data_analysis.html#influenza-type-and-sub-type-identification-and-human-betacoronavirus-classification-as-of-march-2020 (see also the list of current genetic markers used for classification).
  • The publicly available SARS-CoV-2 reference genome sequence (NCBI accession number MN908947 https://www.ncbi.nlm.nih.gov/nuccore/MN908947) is available in the default INSaFLU reference database (several sequence versions with differential trimming of the sequence boundaries are available, as these regions might not be captured by your wet-lab NGS strategy). As before, the users can still insert their own reference sequences.
  • Maximum size per fastq.gz file remains 300 MB, but files will be downsized to ~150 MB before analysis (and not ~50 MB, as previously). This change minimizes the risk of losing considerable depth of coverage in your analysis, specially for SARS-CoV-2 genome analysis.

January 15, 2020

  • INSaFLU now allows you to easily color tree nodes and to display colored metadata blocks near to the phylogenetic trees

This update largely facilitates the visualization, exploration and interpretation of your phylogenetic data, while potentiating the association/integration of relevant epidemiological and/or clinical data and pathogen genomic data towards an enhanced laboratory surveillance. See how to do it here: https://insaflu.readthedocs.io/en/latest/output_visualization.html#b-navigate-through-phylogenetic-trees-and-explore-your-metadata

  • INSaFLU also allows you to “Add/update Sample metadata” at any time

To take advantage of the novel metadata visualization tools, you can now add/update the samples descriptive data by simply uploading a comma-separated (.csv) or tab-separated (.tsv or .txt) table with the updated data (a template file is provided in Samples menu / Add or Update Samples from csv / tsv file). Specific documentation can be found here: https://insaflu.readthedocs.io/en/latest/uploading_data.html#updating-sample-metadata

January 10, 2020

  • The INSaFLU list of genetic markers “influenza_assign_segments2contigs” was upgraded (now includes 544 sequences). This update allows the rapid assignment of additional representative virus of distinct genetic clades, which, for instance, can facilitate the sub-group HA classification and potentiate the detection of (intra-subtype) reassortments.

Latest database can be downloaded here: INSaFLU_current_genetic_markers_v5_after_10_01_2020.xlsx

All database versions can be found here: https://insaflu.readthedocs.io/en/latest/data_analysis.html?highlight=genetic_markers#type-and-sub-type-identification

  • The default reference database of INSaFLU was also updated. All reference sequences at INSaFLU are publicly available at NCBI (or are made available under permission of the authors).

Download the current list here: INSaFLU_current_REFERENCE_DATABASE_10_01_2020.xlsx)

Instructions to upload additional reference sequences (e.g., “vaccine-like” sequences available in GISAID) to your confidential account can be found here: https://insaflu.readthedocs.io/en/latest/uploading_data.html#uploading-reference-data

2019

January 02, 2019

  • The INSaFLU list of genetic markers “influenza_assign_segments2contigs” was upgraded (now includes 464 sequences), so, from now one, INSaFLU can assign additional representative virus of distinct genetic sub-groups of seasonal A(H3N2) viruses, not only facilitating the sub-group HA classification, but also potentiating the detection of (intra-subtype) reassortments.

Latest database can be downloaded here: INSaFLU_current_genetic_markers_v4_after_02_01_2019.xlsx

All database versions can be found here: https://insaflu.readthedocs.io/en/latest/data_analysis.html?highlight=genetic_markers#type-and-sub-type-identification

2018

October 30, 2018

  • Original reads (i.e., reads uploaded) will now be deleted after 10 days of their upload. In fact, after quality analysis and improvement, the INSaFLU pipeline does not use those original reads for any other downstream analysis (quality reports and derived quality processed reads will remain available for download).

June 29, 2018

INSaFLU now published in Genome Medicine.

Borges V, Pinheiro M et al. Genome Medicine (2018) 10:46

https://doi.org/10.1186/s13073-018-0555-0

May 14, 2018

  • The INSaFLU list of genetic markers “influenza_assign_segments2contigs” was upgraded (now includes 416 sequences), so, from now one, INSaFLU can assign additional close references sequences to your viruses, such as representative virus of distinct genetic sub-groups or seasonal A(H3N2) viruses or representative A(H5N1) sequences of distinct H5 genetic clades.

All database versions can be found here: https://insaflu.readthedocs.io/en/latest/data_analysis.html?highlight=genetic_markers#type-and-sub-type-identification

April 9, 2018

  • Maximum size per fastq.gz file was upgraded from 50 MB to 300 MB.

  • The draft assembly provided by INSaFLU (FASTA format) now additionally includes potential non-influenza specific contigs (i.e., contigs not assigned to any influenza segment / reference by INSaFLU). This feature allows users to better inspect the draft assemblies and reinforces the applicability of INSaFLU for other viruses.

March 9, 2018

  • INSaFLU now provides a draft genome assembly (FASTA format) including influenza-specific NODES/contigs. These are identified by screening the SPAdes-derived draft assemblies against an in house database using ABRIcate, which allows assigning NODES/contigs to the corresponding viral segments and to a related reference influenza virus (output: table in “.tsv” format). Please check these new outputs and guide to interpret them at the INSaFLU tab “Samples” / “Extra info” / “Type and subtype/lineage identification”. Please also check software settings and parameters at the “Data analysis” tab of this Documentation.

    This new feature reinforces the application of INSaFLU to:

    • analyse viruses for which a close related whole-genome sequence is not available (e.g., avian influenza) at the INSaFLU or other databses (NCBI, GISAID, etc);
    • investigate reassortments
    • disclose mixed infections

January 25, 2018

  • INSaFLU 1.0.0 is released for the scientific community at https://insaflu.insa.pt

    INSaFLU (“INSide the FLU”) is an bioinformatics free web-based suite that deals with primary NGS 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. While INSaFLU has indeed some influenza-specific features (e.g., automatic type/subtype identification), there is no restrictions to use it for other viruses.

    Main highlights:

    • open to all, free of charge, user-restricted accounts
    • applicable to NGS data collected from any amplicon-based schema
    • allows advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics
    • automatic identification of influenza type and subtype/lineage, detection of putative mixed infections and intra-host minor variants
    • allows integrating data in a cumulative manner, thus fitting the analytical dynamics underlying the continuous epidemiological surveillance during flu epidemics
    • outputs are provided in nomenclature-stable and standardized formats and can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis and visualization