Pathway Module API Documentation

Pathway Module API Documentation#

This document provides an overview of the pathway.py module, which includes classes and functions for pathway analysis using gprofiler.

Classes#

Pathways

A class to represent pathways loaded from a gmt file.

Pathways#

  • Description: Class to represent pathways loaded from a gmt file.

Functions#

read_gmt_file#

  • Description: Read gmt file and return a dataframe with pathway id as index and gene set as value.

  • Parameters:

    • gmt_file: Path to the gmt file.

  • Returns: DataFrame with pathway id as index and gene set as value.

get_tf_pathway#

  • Description: Get pathway for a pair of transcription factors.

  • Parameters:

    • tf1: First transcription factor.

    • tf2: Second transcription factor.

    • cell: Cell object containing gene annotations.

    • filter_str: Filter string for pathway analysis.

  • Returns: Tuple containing gene sets and filtered pathway data.

plot_geneset#

  • Description: Plot gene set expression.

  • Parameters:

    • intersect_genes: List of intersect genes.

    • ng_ball_exp: DataFrame of gene expression.

    • geneset: List of genes in the gene set.

    • geneset_name: Name of the gene set.

    • sample_category_name: Name of the sample category.

  • Returns: A plot of gene set expression.

fisher_exact_test#

  • Description: Perform Fisher’s exact test.

  • Parameters:

    • set1: List of genes in the first set.

    • set2: List of genes in the second set.

    • background: List of genes in the background.

  • Returns: Tuple containing the p-value, fold enrichment, and odds ratio.

hypergeometric_test#

  • Description: Perform hypergeometric test.

  • Parameters:

    • set1: List of genes in the first set.

    • set2: List of genes in the second set.

    • background: List of genes in the background.

  • Returns: Tuple containing the p-value and fold enrichment.

plot_fold_enrichment_with_significance#

  • Description: Plot fold enrichment with significance.

  • Parameters:

    • gene_lists: List of gene lists.

    • gene_list_names: List of gene list names.

    • df_genes: DataFrame of genes.

    • gene_annot: DataFrame of gene annotations.

    • ax: Axes to plot on.

  • Returns: Axes with the plot.

Usage#

The pathway.py module is designed to be used in genomic data analysis pipelines where pathway analysis is required. It provides a comprehensive set of tools for analyzing pathways and gene sets.

For more detailed usage examples, refer to the tutorials and examples provided in the documentation.