Momi

Introduction

momi (MOran Models for Inference) is a Python package that computes the expected sample frequency spectrum (SFS), a statistic commonly used in population genetics, and uses it to fit demographic history.

For more information, please check:

Versions

  • 2.1.19

Commands

  • python

  • python3

Module

You can load the modules by:

module load biocontainers
module load momi

Interactive job

To run momi interactively on our clusters:

(base) UserID@bell-fe00:~ $ sinteractive -N1 -n12 -t4:00:00 -A myallocation
salloc: Granted job allocation 12345869
salloc: Waiting for resource configuration
salloc: Nodes bell-a008 are ready for job
(base) UserID@bell-a008:~ $ module load biocontainers momi
(base) UserID@bell-a008:~ $ python
Python 3.9.7 (default, Sep 16 2021, 13:09:58)
[GCC 7.5.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import momi
>>> import logging
>>> logging.basicConfig(level=logging.INFO,
                 filename="tutorial.log")
>>> model = momi.DemographicModel(N_e=1.2e4, gen_time=29,
                           muts_per_gen=1.25e-8)

Batch job

Warning

Using #!/bin/sh -l as shebang in the slurm job script will cause the failure of some biocontainer modules. Please use #!/bin/bash instead.

To run momi on our clusters:

#!/bin/bash
#SBATCH -A myallocation     # Allocation name
#SBATCH -t 1:00:00
#SBATCH -N 1
#SBATCH -n 1
#SBATCH --job-name=momi
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out

module --force purge
ml biocontainers momi

python python.py