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XgenePy

XgenePy is a Python port of the XgeneR package for modeling cis and trans regulatory differences between homozygous strains. It mirrors the core XgeneR workflow while replacing the R edgeR dependency with the Python edgePython package.

The package centers on:

  • building the same allele-aware design matrices used by XgeneR
  • fitting negative binomial GLMs with edgepython
  • testing cis and trans hypotheses
  • generating the same assignment and proportion-cis summaries
  • producing diagnostic plots in matplotlib

Install

Create the conda environment:

conda env create -f environment.yaml
conda activate xgenepy

Then install the package in editable mode:

pip install -e .

Example

import pandas as pd
from xgenepy import FitObject, fit_edgepython, get_assignments_and_plot

counts = pd.read_csv("../XgeneR/inst/extdata/BATcold_ballinger_counts.csv", index_col=0)
metadata = pd.read_csv("../XgeneR/inst/extdata/BATcold_ballinger_metadata.csv", index_col=0)

fit_obj = FitObject(counts=counts, metadata=metadata, trans_model="log_additive")
fit_obj = fit_edgepython(fit_obj)

results = get_assignments_and_plot(fit_obj, make_plot=False)
print(results.dataframe.head())

Project Layout

  • src/xgenepy/model.py: model construction, design matrices, contrasts, and fitting
  • src/xgenepy/plotting.py: plotting and assignment helpers
  • data/: copied example datasets from XgeneR, including BATcold, cold, and full Ballinger files
  • notebooks/: Jupyter notebook equivalents of the XgeneR vignettes
  • tests/: pytest coverage for design and fitting smoke tests
  • scripts/: example script for running the BATcold dataset

Reference

The XgenePy method is described in

Ingileif B. Hallgrímsdóttir, Maria Carilli, Lior Pachter, Estimating cis and trans contributions to differences in gene regulation, bioRxiv, 2024, doi.org/10.1101/2024.07.13.603403.