BayeScan
BayeScan aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. The analysis is based on the multinomial-Dirichlet model.
License
Free to use and open source under GNU GPLv3
Available
- Roihu-CPU: 2.1
Usage
To use BayeScan, first run command
After that you can launch BayeScan with a command like:
With bayescan_2.1, it is important to define the number of threads always explicitly. This is because, by default, BayeScan tries to use all available cores.
On Roihu, BayeScan tasks should be executed as batch jobs. Below is a sample batch job file for BayeScan:
#!/bin/bash
#SBATCH --job-name=bayescan
#SBATCH --account=project_XXXXXX
#SBATCH --time=08:00:00
#SBATCH --mem=6G
#SBATCH --partition=small
#SBATCH --cpus-per-task=4
#SBATCH --nodes=1
#SBATCH --ntasks=1
# Set the number of threads based on cpus-per-task
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK:-1}
# Place and bind threads to single cores
# Comment the following lines if binding is not desired
export OMP_PLACES=cores
export OMP_PROC_BIND=spread
module load bayescan
bayescan_2.1 -threads ${SLURM_CPUS_PER_TASK} test_binary_AFLP.txt > bayescan_omp.out
The script above reserves 8 hours of computing time, 6 GB of memory and 4 computing cores. The project_XXXXXX in the --account definition should be replaced with the project name of your computing project.
The job can be submitted to the batch job system with command:
In many cases BayeScan will not benefit from using more than 8 cores, so check performance if using more.
More instructions for running batch jobs can be found in CSC batch job instructions