Oncoplot Example¶

This notebook demonstrates the oncoplot() visualization, which displays somatic mutation patterns across genes and samples. The plot combines a mutation matrix with TMB per sample and gene alteration frequency panels.

For detailed documentation, see the Oncoplot API Reference.

Load Data¶

Load the MAF file and create a PyMutation object. The example uses the TCGA-LAML dataset.

In [1]:

from pyMut.input import read_maf


maf_path = "../../../src/pyMut/data/examples/MAF/tcga_laml.maf.gz"
print(f'📂 Loading file: {maf_path}')

# Read the MAF file and create the PyMutation object
py_mutation = read_maf(maf_path,assembly="37")

from pyMut.input import read_maf maf_path = "../../../src/pyMut/data/examples/MAF/tcga_laml.maf.gz" print(f'📂 Loading file: {maf_path}') # Read the MAF file and create the PyMutation object py_mutation = read_maf(maf_path,assembly="37")

2025-11-16 19:02:04,143 | INFO | pyMut.input | Starting MAF reading: ../../../src/pyMut/data/examples/MAF/tcga_laml.maf.gz
2025-11-16 19:02:04,143 | INFO | pyMut.input | Loading from cache: ../../../src/pyMut/data/examples/MAF/.pymut_cache/tcga_laml.maf_0c3d83642d761cde.parquet
2025-11-16 19:02:04,172 | INFO | pyMut.input | Cache loaded successfully in 0.03 seconds

📂 Loading file: ../../../src/pyMut/data/examples/MAF/tcga_laml.maf.gz

Configure Plot Settings¶

Enable high-quality rendering settings for publication-ready figures.

In [2]:

py_mutation.configure_high_quality_plots()

py_mutation.configure_high_quality_plots()

Generate Oncoplot¶

The oncoplot() function creates a comprehensive visualization with four panels:

• Center panel: Mutation matrix showing gene-sample mutation status
• Top panel: Tumor Mutation Burden (TMB) per sample
• Right panel: Gene alteration frequency with percentage labels
• Bottom panel: Variant classification legend

Parameters:

• figsize: Figure size as (width, height) in inches. Default: (16, 10)
• title: Plot title. Default: "Oncoplot"
• gene_column: Column name for gene symbols. Default: "Hugo_Symbol"
• variant_column: Column name for variant classifications. Default: "Variant_Classification"
• ref_column: Column name for reference alleles. Default: "REF"
• alt_column: Column name for alternative alleles. Default: "ALT"
• top_genes_count: Number of top mutated genes to display. Default: 10
• max_samples: Maximum number of samples to display. Default: 180

In [3]:

py_mutation.oncoplot()

py_mutation.oncoplot()

Oncoplot generated: 10 genes × 193 samples (5.07s)

Out[3]: