Assembly pipeline of CIWARS for computing resistome risk and identifying ARG like sequencs and their mobility
- Linux operating system
- conda
git clone https://github.com/muhit-emon/Assembly_Pipeline.git cd Assembly_Pipeline bash install.sh conda env create -f environment.yml
After installation, a conda environment named assembly_pipeline will be created.
To activate the environment, run the following command
conda activate assembly_pipeline
Download the compressed Blast Database file from Zenodo (25 GB) to run MetaCompare and uncompress it
Go inside Assembly_Pipeline directory
wget https://zenodo.org/records/10471551/files/BlastDB.tar.gz tar -zxvf BlastDB.tar.gz
Download the compressed DeepARG-DB and mobileOG database (DB.tar.gz) from one drive, put it inside the "Assembly_Pipeline" directory and uncompress it
Go to One Drive and download DB.tar.gz. Put it inside the Assembly_Pipeline directory and uncompress it.
tar -zxvf DB.tar.gz
Go inside Assembly_Pipeline directory.
To run the assembly pipeline on metagenomic paired-end short read data ( * .fastq/ * .fq/ * .fastq.gz/ * .fq.gz), use the following command
nextflow run assembly_pipeline.nf --R1 <absolute/path/to/forward/read/file> --R2 <absolute/path/to/reverse/read/file> --out_fname <prefix of output file name> rm -r work
The command line options for this script (assembly_pipeline.nf) are:
--R1: The absolute path of the fastq file containing forward read sequences
--R2: The absolute path of the fastq file containing reverse read sequences
--out_fname: The prefix of the output file name
With --out_fname S1, three output files named S1_resistome_risk.txt, S1_ARGs.faa, and S1_ARGs_and_mobility.tsv will be generated inside Assembly_Pipeline directory.