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54 lines
2.4 KiB
Bash
54 lines
2.4 KiB
Bash
#!/bin/bash
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## Last updated Jan 2025 by Auden Cote-L'Heureux
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## This script is intended to be used to process genomic CDS with EukPhylo part 1 on an HPC that uses the Slurm workload manager.
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## The first part of the script are Slurm-specific parameters that should be adjusted by users to fit their resource allocation
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## needs and restrictions, followed by some example commands taken from the GitHub Wiki, more detail for which can be found
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## here: https://github.com/Katzlab/EukPhylo/wiki/EukPhylo-Part-1:-GF-assignment
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############### FOR SMITH GRID HPC ###############
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## Slurm specific code
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#SBATCH --job-name=EukPhylo
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#SBATCH --output=EukPhylo.%j.out # Stdout (%j expands to jobId)
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#SBATCH --nodes=1
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#SBATCH --ntasks=1
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#SBATCH --ntasks-per-node=1 ##change to number of srun when running multiple instances
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#SBATCH --mem=160G
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#SBATCH --mail-type=ALL
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#SBATCH --mail-user=email@xxx.edu ##add your email address for job updates
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module purge #Cleans up any loaded modules
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module load slurm
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module load tqdm/4.62.3-GCCcore-11.2.0
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module load Biopython/1.79-foss-2021b
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module load BLAST+/2.12.0-gompi-2021b
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module load DIAMOND/2.0.13-GCC-11.2.0
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module load VSEARCH/2.22.1-GCC-11.3.0
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############### FOR UMASS UNITY HPC ###############
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## Slurm specific code
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#SBATCH --job-name=EukPhylo
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#SBATCH --output=EukPhylo.%j.out # Stdout (%j expands to jobId)
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#SBATCH --nodes=1
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#SBATCH --ntasks=1
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#SBATCH --ntasks-per-node=64
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#SBATCH --mem=40G
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#SBATCH --mail-type=ALL
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#SBATCH --mail-user=email@xxx.edu
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module purge #Cleans up any loaded modules
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module use /gridapps/modules/all
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module load conda/latest
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module load uri/main
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module load diamond/2.1.7
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module load VSEARCH/2.22.1-GCC-11.3.0
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conda activate /work/pi_lkatz_smith_edu/Conda_PTL6p1
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parent='/Your/Home/Folder/'
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## Example commands
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# A simple run that goes from script 1 to script 7 (the last script) using the Universal genetic code
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srun -D ${parent}Scripts python3 ${parent}Scripts/wrapper.py --first_script 1 --last_script 7 --assembled_transcripts ${parent}AssembledTranscripts -o ${parent}Out --genetic_code ${parent}Gcode.txt --databases ${parent}Databases > log.out
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# Including the cross-plate contamination step, using conspecific names
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srun -D ${parent} python3 ${parent}Scripts/wrapper.py --first_script 1 --last_script 7 --assembled_transcripts ${parent}AssembledTranscripts --output . --genetic_code ${parent}Gcode.txt --databases ${parent}Databases --xplate_contam --conspecific_names ${parent}Conspecific.txt > log.out
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