Install dependencies

We need the following three tools for this SOP:

• snakemake (version >= 7.25.0)
• snakedeploy (version >= 0.8.6)

First lets install mamba:

conda install -c conda-forge  -n base mamba

Second lets create new conda environment using mamba for this tutorial:

mamba create -c bioconda -c conda-forge --name snakemake snakemake snakedeploy

Note: When you install the environment you will only need to activate the environment to run the workflow no need to install it again

Deploy the workflow

To deploy the workflow you need first to activate the environment

conda activate snakemake

Then you will need to deploy the workflow depending on the release you want

# Path were you want to deploy the workflow
mkdir /path/to/where/you/want/to/deploy/the/workflow

# Command line to deploy the workflow in this folder
snakedeploy deploy-workflow https://github.com/rdenise/detection_virus_metagenomes /path/to/where/you/want/to/deploy/the/workflow --tag 0.0.1

Preparation of the config file

Now that the workflow is deployed. In the folder where you created, there is a file named ```config/config.yaml

path to contigs reads folder

reads_folder: Here you write the path of the reads folder

identifier of the sample name in the reads files (e.g. _R if the file is named sample1_R1.fastq.gz)

reads_identifier: Here you indicate what separate the name of the sample and the sens of the read (e.g. "R" if the file is name sample1_R1.fastq.gz or "" if the file is name sample1_1.fastq.gz)

If you want the workflow to start after the read assembly you need to indicate the folder of your assemble contigs

path to contigs folder if you already done the assembly

assemble_contigs: path of the assemble contigs

Exention of the contig file (e.g. fasta)

contigs_ext: extension of the fasta file (e.g. fasta, fa, fna...)

Note: If you want to start at the assembly steps, just let the value empty with a ""For the databases for the virus identification only ICTV, refseq viral, IMG/VR and crassphage are mandatory. If you want to add more database add your database to the list in this format```
name_of_the_database:
    path: path/to/the/database/fasta/nucleotide/file

Note: everything in the config file could be change and if you miss a value for some mandatory item, the workflow will raise an error

Activate the snakemake environment

Before running the workflow make sure that the conda environment is activated

conda activate snakemake

And that you are in the folder where the workflow is deployed

Run snakemake workflow

Now everything is configure, you just have to run:

snakemake --cores 10 --use-conda

The workflow will do all the steps for you and install all the needed software.

When the workflow is done running. You will have a output folder looking like that

[output_name]                          <- Main results folder
├── databases                          <- Folder containing databases used in the analysis
│   ├── checkv_db                      <- CheckV database for viral genome completeness and contamination assessment
│   ├── contigs                        <- Folder containing contig FASTA files
│   └── reads_trimmed                  <- Folder containing trimmed read FASTQ files
├── logs                               <- Folder containing log files for each analysis step
├── processed_files                    <- Folder containing processed files resulting from the analysis
│   ├── assemblies                     <- Folder containing assembled contigs
│   ├── blast                          <- Folder containing BLAST output files
│   ├── bowtie2                        <- Folder containing Bowtie2 output files
│   ├── checkv                         <- Folder containing CheckV output files
│   ├── genomad                        <- Folder containing downloaded GenomAD data
│   ├── otu                            <- Folder containing OTU clustering output files
│   └── samtools                       <- Folder containing Samtools output files
├── qc                                 <- Folder containing quality control reports
│   ├── fastqc                         <- FastQC report files for each input read file
│   ├── multiqc_report.trimmed_data    <- MultiQC report for trimmed reads
│   └── multiqc_report.untrimmed_data  <- MultiQC report for untrimmed reads
└── results                            <- Folder containing final analysis results
    ├── bacphlip_out                   <- Output files for BacPhlip viral protein prediction tool
    ├── iphop                          <- Output files for IPHOP prophage prediction tool
    ├── taxonomy                       <- Folder containing taxonomy assignment output files
    └── viral_contigs                  <- Folder containing viral contigs identified in the analysis