.. pycmplot documentation master file

pycmplot
========

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----

**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
--------

.. toctree::
   :maxdepth: 2
   :caption: Getting Started

   installation
   quickstart

.. toctree::
   :maxdepth: 2
   :caption: User Guide

   cli
   python_api_notebook

.. toctree::
   :maxdepth: 2
   :caption: API Reference

   api/index

.. toctree::
   :maxdepth: 1
   :caption: Project Info

   changelog
   contributing
   license

Indices and tables
------------------

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`