viralassembly

A generic viral assembly and QC pipeline which utilises a re-implementation of the artic pipeline to separate out the individual steps allowing greater control on tool versions along with how data is run through the processes. This pipeline can be used as a starting point for analyses on viruses without dedicated workflows already available.

This pipeline is intended to be run on either Nanopore Amplicon Sequencing data or Basic Nanopore NGS Sequencing data that can utilize a reference genome for mapping variant calling, and other downstream analyses. It generates variant calls, consensus sequences, and quality control information based on the reference. To do this, there are three different variant callers that can be utilized which includes: clair3, medaka, and nanopolish (For R9.4.1 flowcells and below only).

Some of the goals of this pipeline are: 1. Rework the artic nanopore pipeline steps as nextflow modules to deal with specific bugs and version incompatibilities - Example: BCFtools consensus error seen in artic pipeline sometimes - Allows adding in clair3 as a new variant calling tool - Potentially eventually work to remove artic as a dependency 2. Allow the pipeline to be used on other viruses with or without amplicon schemes - Due to the QC steps there is unfortunately a current limitation at working with segmented viruses - The pipeline will automatically exit after assembly and not generate QC and Reports for these at this time - This will hopefully be fully implemented at some point in the future 3. Provide Run level and Sample level final reports

Index

• Installation
• Base Run Commands
  • Nanopore - Clair3
  • Nanopore - Medaka
  • Nanopore - Nanopolish
• Outputs
• Limitations
• Citations
• Contributing
• Legal

Installation

1. Download and install nextflow

   1. Download and install with conda
      • Conda command: conda create on nextflow -c conda-forge -c bioconda nextflow
   2. Install with the instructions at https://www.nextflow.io/

2. Run the pipeline with one of the following profiles to handle dependencies (or use your own profile if you have one!):

   • conda
   • mamba
   • singularity
   • docker

Running Commands

Simple commands to run input data. Input data can be done in three different ways: 1. Passing --fastq_pass </PATH/TO/fastq_pass> where fastq_pass is a directory containing barcode## subdirectories with fastq files 2. Passing --fastq_pass </PATH/TO/fastqs> where fastqs is a directory containing .fastq* files 3. Passing --input <samplesheet.csv> where samplesheet.csv is a CSV file with two columns 1. sample - The name of the sample 2. fastq_1 - Path to one fastq file per sample in .fastq* format

The basic examples will show how to run the pipeline using the --fastq_pass input but it could be subbed in for the --input CSV file if wanted.

All detailed running information is available in the usage docs

Nanopore - Clair3

Running the pipeline with Clair3 for variant calls requires fastq files and a clair3 model. When running, the pipeline will either: - Look for subdirectories off of the input "--fastqpass" directory called barcode## to be used in the pipeline - Look for fastq files in the input "--fastqpass" directory called *.fastq* to be used in the pipeline

This pipeline utilizes the same steps as the artic fieldbioinformatics minion pipeline but with each step run using nextflow to allow clair3 to be easily slotted in. See the clair3 section of the usage docs for more information

Basic command: bash nextflow run /PATH/TO/artic-generic-nf/main.nf \ -profile <PROFILE(s)> \ --variant_caller 'clair3' \ --fastq_pass </PATH/TO/fastq_pass> \ --reference <REF.fa> \ <OPTIONAL INPUTS>

Optional inputs could include: - Amplicon scheme instead of just a reference fasta file - Metadata - Filtering options - Running SnpEff for variant consequence prediction - Output reporting options

Nanopore - Medaka

Running the pipeline with medaka for variant calls requires fastq files and a medaka model. When running, the pipeline will either: - Look for subdirectories off of the input "--fastqpass" directory called barcode## to be used in the pipeline - Look for fastq files in the input "--fastqpass" directory called *.fastq* to be used in the pipeline

See the medaka section of the usage docs for more information

Basic command: bash nextflow run /PATH/TO/artic-generic-nf/main.nf \ -profile <PROFILE(s)> \ --variant_caller 'medaka' \ --fastq_pass </PATH/TO/fastq_pass> \ --medaka_model <Medaka Model> \ --reference <REF.fa> \ <OPTIONAL INPUTS>

Optional inputs could include: - Amplicon scheme instead of just a reference fasta file - Metadata - Filtering options - Using base artic minion instead of nextflow implementation - Running SnpEff for variant consequence prediction - Output reporting options

Medaka model information can be found here

Nanopore - Nanopolish

Running the pipeline with nanopolish for variant calls requires fastq files, fast5 files, and the sequencing summary file instead of providing a model. As such, nanopolish requires that the read ids in the fastq files are linked by the sequencing summary file to their signal-level data in the fast5 files. This makes it a lot easier to run using barcoded directories but it can be run with individual read files

See the nanopolish section of the usage docs for more information

Basic command: bash nextflow run /PATH/TO/artic-generic-nf/main.nf \ -profile <PROFILE(s)> \ --variant_caller 'nanopolish' \ --fastq_pass </PATH/TO/fastq_pass> \ --fast5_pass </PATH/TO/fast5_pass> \ --sequencing_summary </PATH/TO/sequencing_summary.txt> \ --reference <REF.fa> <OPTIONAL INPUTS>

Optional inputs could include: - Amplicon scheme instead of just a reference fasta file - Metadata - Filtering options - Using base artic minion instead of nextflow implementation - Running SnpEff for variant consequence prediction - Output reporting options

Outputs

Outputs are separated based off of their tool or file format and found in the results/ directory by default.

Outputs include: - Consensus fasta files - VCF files - Bam files - HTML summary files (either custom or MultiQC)

More output information on pipeline steps and output files can be found in the output docs

Limitations

Current limitations include:

1. Nanopore data only at this time
2. Currently runs for viruses using a reference genome
   • Segmented viruses will exit before the QC section for now
3. Custom report can only work when running with conda
4. SnpEff issues in running and database building/downloading
   • Database building/downloading requires one of three things:
     • The reference ID is in the SnpEff database
       • This allows the database to be downloaded
     • A gff3 file
       • This is used with the reference sequence to build a database
     • A well annotated NCBI genome matching the reference ID
       • This will pull the genbank file and use that to build a database
   • Running SnpEff with singularity sometimes leads to a lock issue which is hopefully fixed

Citations

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x. In addition, references of tools and data used in this pipeline are as follows:

Detailed citations for utilized tools are found in citations.md

Contributing

Contributions are welcome through creating PRs or Issues

Legal

Copyright 2023 Government of Canada

Licensed under the MIT License (the "License"); you may not use this work except in compliance with the License. You may obtain a copy of the License at:

https://opensource.org/license/mit/

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.