Installation
A containerized version of the Segpy pipeline is publicly available from Zenodo, which includes the code, libraries, and dependicies required for running the analyses. The container is compatible with High-Performance Computing (HPC) systems, Linux workstations, or any PC with Bash and Singularity installed.
To use the Segpy pipeline, the folowing must be installed on your system:
Apptainer
segpy.pip is packaged and tested with Apptainer (formerly Singularity) version 1.2.4. Before proceeding, ensure that Apptainer/Singularity is installed on your system. If you are using an HPC system, Apptainer is likely already installed, and you will simply need to load the module. If you encounter any issues while loading the Apptainer module, please contact your system administrator. Before running the Segpy pipeline, load the Apptainer module using the following command:
# Load Apptainer
module apptainer/1.2.4
Segpy.pip
To download the latest version of Segpy run the following command:
# Download the Segpy container
curl "https://zenodo.org/records/14503733/files/segpy.pip.zip?download=1" --output segpy.pip.zip
# Unzip the Segpy container
unzip segpy.pip.zip
To ensure that segpy.pip is downloaded properly, run the following command:
bash /path/to/segpy.pip/launch_segpy.sh -h
If segpy.pip is downloaded properly, the above command should return the folllowing:
------------------------------------
segregation pipeline version 0.0.6 is loaded
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Usage: segpy.pip/launch_segpy.sh [arguments]
mandatory arguments:
-d (--dir) = Working directory (where all the outputs will be printed) (give full path)
-s (--steps) = Specify what steps, e.g., 2 to run just step 2, 1-3 (run steps 1 through 3). 'ALL' to run all steps.
steps:
0: initial setup
1: create hail matrix
2: run segregation
3: final cleanup and formatting
optional arguments:
-h (--help) = Get the program options and exit.
--jobmode = The default for the pipeline is local. If you want to run the pipeline on slurm system, use slurm as the argument.
--analysis_mode = The default for the pipeline is analysing single or multiple family. If you want to run the pipeline on case-control, use case-control as the argumnet.
--parser = 'general': to general parsing, 'unique': drop multiplicities
-v (--vcf) = VCF file (mandatory for steps 1-3)
-p (--ped) = PED file (mandatory for steps 1-3)
-c (--config) = config file [CURRENT: "/scratch/fiorini9/segpy.pip/configs/segpy.config.ini"]
-V (--verbose) = verbose output
-------------------
For a comprehensive help, visit https://neurobioinfo.github.io/segpy/latest/ for documentation.
After successfully downloading segpy.pip we can proceed with the segregation analysis.