Apr 04, 2023
Viruses identification in metagenomes
- 1APC Microbiome Ireland & School of Microbiology, University College Cork, Co. Cork, Ireland.
Protocol Citation: Remi Denise 2023. Viruses identification in metagenomes . protocols.io https://dx.doi.org/10.17504/protocols.io.36wgqjk43vk5/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: In development
We are still developing and optimizing this protocol
Created: March 28, 2023
Last Modified: April 04, 2023
Protocol Integer ID: 79566
Funders Acknowledgement:
ERC
Grant ID: PHAGENET
Abstract
This protocol shows how to use this virus identification workflow (doi: 10.5281/zenodo.7778392) and some manual curation criteria for viral sequence identification in metagenomes.
Before start
This tutorial requires Unix OS with "conda" installed. If you cannot access any Unix OS, you can use virtual machines such as VirtualBox or Vagrant in Windows. If you do not "conda" installed, you can follow the instructions here.
Install dependencies and prep test data
Install dependencies and prep test data
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
The important things to change in the file is:
# 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
Run the workflow
Run the workflow
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.
Results
Results
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