Influenza A&B typing and analysis from Nanopore data.
Influenza is a single-stranded RNA virus and contains a 13.5-14.5kb genome which is split into 8 segments encoding 10-14 proteins (dependent on strain).
The virus is classified using two proteins found on the outer surface of the viral capsid. You’ve probably heard of H1N1 Influenza for example. The H represents hemagglutinin and the N is neuraminidase.
This analysis workflow can be used with Oxford Nanopore Technologies sequencing data from amplified segments of the Influenza Type A and Type B genomes, to determine the most likely strain of Influenza to which the sequenced sample belongs.
Recommended requirements:
- CPUs = 32
- Memory = 32GB
Minimum requirements:
- CPUs = 4
- Memory = 2GB
Approximate run time: 30 minutes when number of cores >= samples
ARM processor support: False
These are instructions to install and run the workflow on command line. You can also access the workflow via the EPI2ME Desktop application.
The workflow uses Nextflow to manage compute and software resources, therefore Nextflow will need to be installed before attempting to run the workflow.
The workflow can currently be run using either
Docker
or Singularity
to provide isolation of the required software.
Both methods are automated out-of-the-box provided
either Docker or Singularity is installed.
This is controlled by the
-profile
parameter as exemplified below.
It is not required to clone or download the git repository in order to run the workflow. More information on running EPI2ME workflows can be found on our website.
The following command can be used to obtain the workflow. This will pull the repository in to the assets folder of Nextflow and provide a list of all parameters available for the workflow as well as an example command:
nextflow run epi2me-labs/wf-flu --help
To update a workflow to the latest version on the command line use the following command:
nextflow pull epi2me-labs/wf-flu
A demo dataset is provided for testing of the workflow. It can be downloaded and unpacked using the following commands:
wget https://ont-exd-int-s3-euwst1-epi2me-labs.s3.amazonaws.com/wf-flu/wf-flu-demo.tar.gz
tar -xzvf wf-flu-demo.tar.gz
The workflow can then be run with the downloaded demo data using:
nextflow run epi2me-labs/wf-flu \
--downsample 50 \
--fastq 'wf-flu-demo/fastq' \
--sample_sheet 'wf-flu-demo/sample_sheet.csv' \
-profile standard
For further information about running a workflow on the command line see https://labs.epi2me.io/wfquickstart/
This workflow is designed to take input sequences that have been produced from Oxford Nanopore Technologies devices using this protocol: (https://community.nanoporetech.com/docs/prepare/library_prep_protocols/ligation-sequencing-influenza-whole-genome) Samples not prepared with this protocol may work sub-optimally or fail to complete succesfully.
This workflow accepts FASTQ files as input.
The FASTQ input parameters for this workflow accept one of three cases: (i) the path to a single FASTQ file; (ii) the path to a top-level directory containing FASTQ files; (iii) the path to a directory containing one level of sub-directories which in turn contain FASTQ files. In the first and second cases (i and ii), a sample name can be supplied with --sample. In the last case (iii), the data is assumed to be multiplexed with the names of the sub-directories as barcodes. In this case, a sample sheet can be provided with --sample_sheet.
(i) (ii) (iii)
input_reads.fastq ─── input_directory ─── input_directory
├── reads0.fastq ├── barcode01
└── reads1.fastq │ ├── reads0.fastq
│ └── reads1.fastq
├── barcode02
│ ├── reads0.fastq
│ ├── reads1.fastq
│ └── reads2.fastq
└── barcode03
└── reads0.fastq
| Nextflow parameter name | Type | Description | Help | Default |
|---|---|---|---|---|
| fastq | string | FASTQ files to use in the analysis. | This accepts one of three cases: (i) the path to a single FASTQ file; (ii) the path to a top-level directory containing FASTQ files; (iii) the path to a directory containing one level of sub-directories which in turn contain FASTQ files. In the first and second case, a sample name can be supplied with --sample. In the last case, the data is assumed to be multiplexed with the names of the sub-directories as barcodes. In this case, a sample sheet can be provided with --sample_sheet. |
|
| analyse_unclassified | boolean | Analyse unclassified reads from input directory. By default the workflow will not process reads in the unclassified directory. | If selected and if the input is a multiplex directory the workflow will also process the unclassified directory. | False |
| Nextflow parameter name | Type | Description | Help | Default |
|---|---|---|---|---|
| sample_sheet | string | A CSV file used to map barcodes to sample aliases. The sample sheet can be provided when the input data is a directory containing sub-directories with FASTQ files. | The sample sheet is a CSV file with, minimally, columns named barcode and alias. Extra columns are allowed. A type column is required for certain workflows and should have the following values; test_sample, positive_control, negative_control, no_template_control. |
| Nextflow parameter name | Type | Description | Help | Default |
|---|---|---|---|---|
| out_dir | string | Directory for output of all workflow results. | output |
| Nextflow parameter name | Type | Description | Help | Default |
|---|---|---|---|---|
| override_basecaller_cfg | string | Override auto-detected basecaller model that processed the signal data; used to select an appropriate Medaka model. | Per default, the workflow tries to determine the basecall model from the input data. This parameter can be used to override the detected value (or to provide a model name if none was found in the inputs). However, users should only do this if they know for certain which model was used as selecting the wrong option might give sub-optimal results. A list of recent models can be found here: https://github.com/nanoporetech/dorado#DNA-models. | |
| reference | string | Enter the full path to a custom reference genome you would like to use. | The workflow defaults to the IRMA consensus reference. This option allows you to specify a path to an alternative reference. | |
| blastdb | string | blastdb file used for typing. | The workflow provides the INSaFLU blastdb. If you would like to supply an alternative then provide the full path to the file here. | |
| min_coverage | integer | Coverage threshold for masking bases in the consensus. | Any bases that are covered below 20x are masked (i.e. represented by 'N') by default in the consensus, this threshold can be changed using this parameter. | 20 |
| min_qscore | number | Minimum read quality score for fastcat. | Any reads which are below quality score of 9 are not used by default. This parameter allows you to customise that. For more information on quality scores please see this blog post: https://labs.epi2me.io/quality-scores | 9 |
| downsample | integer | Number of reads to downsample to in each direction, leave blank for no downsampling. | The workflow for each segment will first filter reads to include only those that are ±10% of the segment length before downsampling to the specified integer (taking an even split from forward and reverse reads). This downsampled data is then used in variant calling. | |
| rbk | boolean | Set when using data created with the RBK protocol. | This prevents shorter reads being filtered out and also turns off downsampling as this is not appropriate for the shorter reads generated with RBK. | False |
Output files may be aggregated including information for all samples or provided per sample. Per-sample files will be prefixed with respective aliases and represented below as {{ alias }}.
| Title | File path | Description | Per sample or aggregated |
|---|---|---|---|
| Workflow report | ./wf-flu-report.html | Easy-to-use HTML report for all samples in the run. | aggregated |
| Typing results | ./wf-flu-results.csv | Typing results in CSV format for onward processing. | aggregated |
| Read alignments | ./{{ alias }}/alignments/align.bam | Read allignments per sample in BAM format. | per-sample |
| Draft consensus FASTA | ./{{ alias }}/consensus/draft.consensus.fasta | Draft consensus sequence. | per-sample |
| Read depth | ./{{ alias }}/coverage/depth.txt | Read depth per base. | per-sample |
| Insaflu typing results | ./{{ alias }}/typing/insaflu.typing.txt | Insaflu abricate typing results. | per-sample |
| Variants file | ./{{ alias }}/variants/variants.annotated.filtered.vcf | Called variants in VCF format. | per-sample |
- Concatenate reads and filter out short reads < 200 bases long
- Align reads to reference with minimap2
- Coverage calculations with samtools)
- Call variants using medaka (medaka blog)
- Make a (coverage masked) consensus with bcftools
- Typing using abricate with the insaflu database, containing the following sequences:
| Database | Gene | Accession | Details |
|---|---|---|---|
| insaflu | M1 | MK576795 | Type_A MK576795 A/England/7821/2019 2019/01/03 7 (MP) |
| insaflu | M1 | AF100378 | Type_B AF100378.1 Influenza B virus B/Yamagata/16/88 segment 7 M1 matrix protein (M) and BM2 protein (BM2) genes, complete cds |
| insaflu | HA | FJ966974 | H1 FJ966974.1 Influenza A virus (A/California/07/2009(H1N1)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | HA | L11142 | H2 L11142.1 Influenza A virus (A/Singapore/1/57 (H2N2)) hemagglutinin (HA) gene, complete cds |
| insaflu | HA | MK576794 | H3 MK576794 A/England/7821/2019 2019/01/03 4 (HA) |
| insaflu | HA | AF285883 | H4 AF285883.2 Influenza A virus (A/Swine/Ontario/01911-2/99 (H4N6)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | HA | EF541403 | H5 EF541403.1 Influenza A virus (A/Viet Nam/1203/2004(H5N1)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | HA | AB295613 | H15 AB295613.1 Influenza A virus (A/duck/Australia/341/83(H15N8)) HA gene for haemagglutinin, complete cds |
| insaflu | NA | GQ377078 | N1 GQ377078.1 Influenza A virus (A/California/07/2009(H1N1)) segment 6 neuraminidase (NA) gene, complete cds |
| insaflu | NA | MK576796 | N2 MK576796 A/England/7821/2019 2019/01/03 6 (NA) |
| insaflu | NA | AB295614 | N8 AB295614.1 Influenza A virus (A/duck/Australia/341/83(H15N8)) NA gene for neuraminidase, complete cds |
| insaflu | HA | AY338459 | H7 AY338459.1 Influenza A virus (A/Netherlands/219/2003(H7N7)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | HA | CY014659 | H8 CY014659.1 Influenza A virus (A/turkey/Ontario/6118/1968(H8N4)) segment 4, complete sequence |
| insaflu | HA | CY014694 | H13 CY014694.1 Influenza A virus (A/gull/Maryland/704/1977(H13N6)) segment 4, complete sequence |
| insaflu | HA | CY018765 | Yamagata CY018765.1 Influenza B virus (B/Yamagata/16/1988) segment 4, complete sequence |
| insaflu | HA | CY103892 | H17 CY103892.1 Influenza A virus (A/little yellow-shouldered bat/Guatemala/060/2010(H17N10)) hemagglutinin (HA) gene, complete cds |
| insaflu | NA | CY103894 | N10 CY103894.1 Influenza A virus (A/little yellow-shouldered bat/Guatemala/060/2010(H17N10)) neuraminidase (NA) gene, complete cds |
| insaflu | NA | CY125730 | N3v2 CY125730.1 Influenza A virus (A/Mexico/InDRE7218/2012(H7N3)) neuraminidase (NA) gene, complete cds |
| insaflu | HA | CY125945 | H18 CY125945.1 Influenza A virus (A/flat-faced bat/Peru/033/2010(H18N11)) hemagglutinin (HA) gene, complete cds |
| insaflu | NA | CY125947 | N11 CY125947.1 Influenza A virus (A/flat-faced bat/Peru/033/2010(H18N11)) neuraminidase-like protein (NA) gene, complete cds |
| insaflu | HA | CY130078 | H12 CY130078.1 Influenza A virus (A/duck/Alberta/60/1976(H12N5)) hemagglutinin (HA) gene, complete cds |
| insaflu | HA | CY130094 | H14 CY130094.1 Influenza A virus (A/mallard/Astrakhan/263/1982(H14N5)) hemagglutinin (HA) gene, complete cds |
| insaflu | NA | CY130096 | N5 CY130096.1 Influenza A virus (A/mallard/Astrakhan/263/1982(H14N5)) neuraminidase (NA) gene, complete cds |
| insaflu | HA | DQ376624 | H6 DQ376624.1 Influenza A virus (A/chicken/Taiwan/0705/99(H6N1)) hemagglutinin (HA) gene, complete cds |
| insaflu | HA | EU293864 | H16 EU293864.1 Influenza A virus (A/black-headed gull/Turkmenistan/13/76(H16N3)) hemagglutinin (HA) gene, complete cds |
| insaflu | HA | FJ183474 | H10 FJ183474.1 Influenza A virus (A/mallard/Bavaria/3/2006(H10N7)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | NA | FJ183475 | N7 FJ183475.1 Influenza A virus (A/mallard/Bavaria/3/2006(H10N7)) segment 6 neuraminidase (NA) gene, complete cds |
| insaflu | NA | GQ907296 | N3v1 GQ907296.1 Influenza A virus (A/black headed gull/Mongolia/1756/2006(H16N3)) segment 6 neuraminidase (NA) gene, complete cds |
| insaflu | HA | GU052203 | H11 GU052203.1 Influenza A virus (A/duck/England/1/1956(H11N6)) segment 4 hemagglutinin (HA) gene, complete cds |
| insaflu | NA | KC853765 | N9 KC853765.1 Influenza A virus (A/Hangzhou/1/2013(H7N9)) segment 6 neuraminidase (NA) gene, complete cds |
| insaflu | HA | KX879589 | H9 KX879589.1 Influenza A virus (A/swine/Hong Kong/9/98(H9N2)) segment 4 hemagglutinin (HA) gene, partial cds |
| insaflu | HA | M58428 | Victoria M58428.1 Influenza B/Victoria/2/87, hemagglutinin (seg 4), RNA |
| insaflu | NA | EU429793 | N4 EU429793.1 Influenza A virus (A/turkey/Ontario/6118/1968(H8N4)) segment 6 neuraminidase (NA) mRNA, complete cds |
| insaflu | NA | EU429795 | N6 EU429795.1 Influenza A virus (A/duck/England/1/1956(H11N6)) segment 6 neuraminidase (NA) mRNA, complete cds |
- Clade and lineage assignment using nextclade
- If the workflow fails please run it with the demo data set to ensure the workflow itself is working. This will help us determine if the issue is related to the environment, input parameters or a bug.
- See how to interpret some common nextflow exit codes here.
If your question is not answered here, please report any issues or suggestions on the github issues page or start a discussion on the community.
Why does the workflow fail, or the report shows very low coverage?
This can happen when users use the workflow on data that has been generate using the RBK protocol instead of the recomended Influenza whole-genome protocol, as a result of RBK's shorter read lengths. Ensure the --rbk flag has been set to prevent over-filtering of reads.
See the EPI2ME website for lots of other resources and blog posts.
