python-environment-management

python-environment-management

Summary

Establish and validate isolated Python environments with pinned dependency versions (numpy ≥1.18.1, scipy ≥1.4.1, pysam ≥0.15.4, bx-python ≥0.8.8) required for Hi-C data processing pipelines. This skill ensures reproducible execution of Python-dependent bioinformatics workflows by verifying interpreter version (>3.7), resolving transitive dependencies, and documenting environment configuration for downstream pipeline steps.

When to use

You are preparing to run Hi-C data normalization or read alignment filtering steps that depend on Python modules (iced, pysam, numpy, scipy) and you need to ensure consistent module versions across multiple runs or compute nodes. Use this skill at the start of any HiC-Pro pipeline execution or when setting up a new computational environment for Hi-C analysis.

When NOT to use

• If Hi-C data has already been normalized using a pre-configured HiC-Pro Docker/Singularity container or conda environment — environment setup is already handled.
• If you are only performing SAM/BAM read alignment filtering without downstream normalization — pysam alone may not require the full iced+numpy+scipy stack.
• If Python 2.x is the only available interpreter and cannot be upgraded — the pipeline requires Python >3.7.

Inputs

• Target system shell environment (bash/sh)
• Python interpreter (>3.7) executable path
• Optional: existing config-install.txt or environment configuration file

Outputs

• Validated Python environment with iced module installed
• Configuration file with PYTHONPATH and dependency paths documented
• Version verification report (Python version, iced version, numpy/scipy versions)

How to apply

First, verify that Python >3.7 is available on the target system by checking the interpreter version. Then, install the iced module independently from https://github.com/hiclib/iced along with its required transitive dependencies (numpy ≥1.18.1, scipy ≥1.4.1) using pip or the module's setup.py. Validate installation by importing each module in a Python interpreter and checking version and API availability. Document the iced installation path and set PYTHONPATH environment variables to point to the installation directory in a configuration file that will be sourced before running HiC-Pro normalization steps. This ensures the ICE normalization algorithm can correctly locate and use the iced module during Hi-C contact matrix correction.