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A self-tuning sliding-window framework for phenotype-linked regional poly-methylation architecture in sparse wildlife methylomes.

Project description

poly-CpG: Sliding window analysis of methylomes

This is a lightweight package to accompany the sliding window method for the analysis of methylomes.

Additional scripts and data can be found in the "Supplementary" branch. Herein the data and code used within the study are provided.

The package call be installed as:

pip install poly_cpg

The program can quickly be performed using the commands:

import poly_cpg as pc

# Load synthetic example data
M, pos, gamma, beta, y, cpg_names = pc.load_example()

# Run sliding-window algorithm
df_windows = pc.self_tuning_windows_dual(M, gamma, beta, pos, y)

# Classify windows
df_windows = pc.classify_windows(df_windows)

print(df_windows.head())

This produces a table of windows with the genomic coordinates, number of CpGs, R^2 values, directional agreement and trust classificaiton

The script folder contains the necessary script for the synthetic data generation.

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