MethylVerse

Library to work with WGBS, EM-seq, and/or methylation array data in one interface.

Install

If you dont already have numpy and scipy installed, it is best to download Anaconda, a python distribution that has them included.

    https://continuum.io/downloads

PyPI install, presuming you have all its requirements installed:

    pip install ngsfragments
	pip install MethylVerse

The developmental version of MethylVerse can also be install from GitHub.

    pip install git+https://github.com/kylessmith/MethylVerse/

First use of the MethylVerse software will initialize a download of necessary reference data. Raw reference data is also available at on Zenodo.

    https://zenodo.org/records/16580408
    https://zenodo.org/records/16581863

Usage

General useage:

import MethylVerse as mv

beta_values = mv.core.read_methylation("path/to/methylation")

classifier = mv.tools.classifiers.MPACT.MPACT_classifier_torch.MPACT_classifier()
predictions = classifier.predict(beta_values)

Run the M-PACT classifier from the cammandline

python -m MethylVerse MPACT example.bedgraph --impute --regress --call_cnvs --verbose

Additional options can be viewed:

python -m MethylVerse MPACT -h

usage: __main__.py MPACT [-h] [--impute] [--regress] [--probability_threshold PROBABILITY_THRESHOLD]
                         [--max_contamination_fraction MAX_CONTAMINATION_FRACTION] [--call_cnvs] [--out OUT] [--verbose]
                         input_data

positional arguments:
  input_data            Input data, idat name, nanopore bed file, or MethylDackel bedGraph

options:
  -h, --help            show this help message and exit
  --impute              Impute data missing CpGs
  --regress             Whether to regress data and remove background CSF/Immune
  --probability_threshold PROBABILITY_THRESHOLD
                        Probability threshold for M-PACT classification (default: 0.7)
  --max_contamination_fraction MAX_CONTAMINATION_FRACTION
                        Max contamination fraction for M-PACT classification (aggressiveness of removing background, default=0.3)
  --call_cnvs           Call CNVs from the methylation file
  --out OUT             Output file
  --verbose             Verbose output