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pavvis is a Python package for analysing and visualising gene Presence/Absence Variation (PAV) data from pangenome studies.

pavvis was designed to be easy to use and optimised for large-scale genomic datasets. To get the best use out of this Python package, we recommend reading through our concepts page, that will help you to understand the data structures associated with all analysis in this Python package.

Plotting modules

Module	Description
Presence	Gene presence frequency histograms and per-sample gene count plots
Curves	Pangenome accumulation curves and Jaccard similarity curves
Variable Genes	Frequency distributions and exclusive gene bar charts
UMAP	2D and 3D UMAP embeddings of sample PAV profiles
Heatmap	PAV matrix and sample similarity heatmaps

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Quick start

from pavvis import PavMatrix
import pavvis.plots as plots

pm = PavMatrix("pav_matrix.csv", "metadata.csv")
print(pm)
# PavMatrix(34295 genes × 1039 samples)

print(pm.gene_counts)
# {'core': 12, 'variable': 28761, 'absent': 5522}

plots.presence_frequency_histogram(pm).show()