This gist has instructions about runnig FunGAP pipeline from inside a Docker Container.
Requirements:
- Docker
- 16Gb of available disk space
- GeneMark-ES/ET release and it's key (
gmes_linux_64.tar.gz
andgm_key_64.gz
)
Be sure you have the following files in the working directory:
Dockerfile fungap.conf gmes_linux_64.tar.gz gm_key_64.gz patch_braker.pl
GeneMark is not free for everybody, so you need to register in order to have gm_* files. If was not for that I could have push FunGAP docker image ready for use in DockerHub. The Dcoker image will have about 13Gb.
# 1. Clone FunGAP repository
git clone https://github.com/CompSynBioLab-KoreaUniv/FunGAP.git
# 2. Go to docker directory
cd FunGAP/docker
# 3. Download gmes_linux_64.tar.gz and gm_key_64.gz and put it in same directory
# 4. Build the image
docker build -t fungap .
-
Go to the directory you have your rna-seq reads and genome fasta.
-
Enter into a docker container of fungap:
docker run -it -w /fungap_workspace --rm -v $(pwd):/fungap_workspace fungap bash
-
Go to
/fungap_workspace
and use helper script to get Augustus species.python /workspace/FunGAP/get_augustus_species.py \ --genus_name "Saccharomyces" \ --email_address [email protected]
-
Make protein database
python /workspace/FunGAP/download_sister_orgs.py \ --taxon "Saccharomyces" \ --email_address [email protected] zcat sister_orgs/*faa.gz > prot_db.faa
-
Run FunGAP
python /workspace/FunGAP/fungap.py \ --output_dir fungap_out \ --trans_read_1 SRR1198667_1.fastq \ --trans_read_2 SRR1198667_2.fastq \ --genome_assembly GCF_000146045.2_R64_genomic.fna \ --augustus_species saccharomyces_cerevisiae_S288C \ --sister_proteome prot_db.faa \ --num_cores 8
Now you can exit docker container. Your current working directory was mounted inside FunGAP container (on /fungap_workspace) so all output files will be available on your system.