# Input file for the automated creation GGA docker stacks # The file consists in a "list" of species for which the script will have to create these stacks/load data into galaxy/run workflows - name: citrus_sinensis description: # Species description, leave blank if unknown or you don't want it to be used # These parameters are used to set up the various urls and adresses in different containers # The script requires at least the genus to be specified genus: Citrus # Mandatory! species: sinensis # Mandatory! sex: male strain: common_name: origin: data: # Paths to the different datasets to copy and import into the galaxy container (as a shared library) # Must be absolute paths to the dataset genome_path: /path/to/repo/examples/src_data/genome/v1.0/Citrus_sinensis-scaffold00001.fasta # Mandatory! transcripts_path: /path/to/repo/examples/src_data/annotation/v1.0/Citrus_sinensis-orange1.1g015632m.g.fasta # Mandatory! proteins_path: # Mandatory! gff_path: /path/to/repo/examples/src_data/annotation/v1.0/Citrus_sinensis-orange1.1g015632m.g.gff3 # Mandatory! interpro_path: /path/to/repo/examples/src_data/annotation/v1.0/functional_annotation/Citrus_sinensis-orange1.1g015632m.g.iprscan.xml orthofinder_path: blastp_path: blastx_path: /path/to/repo/examples/src_data/annotation/v1.0/functional_annotation/Blastx_citrus_sinensis-orange1.1g015632m.g.fasta.0_vs_uniprot_sprot.fasta.out # If the user has several datasets of the same 'nature' (gff, genomes, ...) to upload to galaxy, the next scalar is used by the script to differentiate # between these different versions and name directories according to it and not overwrite the existing data # If left empty, the genome will be considered version "1.0" genome_version: 1.0 # Same as genome version, but for the OGS analysis ogs_version: 1.0 performed_by: services: # List the optional services to be deploy in the stack # By default, only tripal, tripaldb, galaxy, jbrowse and elasticsearch services will be deployed blast: 0