pycmplot
pycmplot is a Python package for generating multi-track circular and linear Manhattan plots from GWAS summary statistics. It accepts any number of per-variant summary statistic files — GWAS, selection scans (iHS, FST, XP-EHH), or any column-delimited p-value table — and produces publication-ready Manhattan plots with automatic gene annotation, lead-SNP extraction, and optional hg19 → hg38 coordinate liftover.
Key features
Multi-track stacked Manhattan plots (linear and Circos-style circular) for comparing GWAS signals across traits, populations, or imputation panels.
QQ plots with 95 % confidence bands, genomic inflation (λ) annotation, log-uniform point thinning for large datasets, and combined / separate / overlay layouts.
Automatic column detection — chromosome, position, SNP ID, p-value, and genome build columns are inferred from common naming conventions.
Lead-SNP and locus annotation — nearest-gene lookup and a structured hits summary table are generated alongside every plot.
Legacy → hg38 liftover — mix coordinate systems in one run; hg18 and hg19 inputs are automatically harmonised to hg38 via
pyliftover.Command-line interface and Python API — use interactively in Jupyter or integrate into a pipeline.
Contents
Getting Started
User Guide
API Reference
Project Info