https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess

Wiki: https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess/wiki

Help documentation: https://christensen-lab-dartmouth.github.io/PyMethylProcess/

Alternatively, you can access the pdf: PyMethylProcess.pdf

What is it:

• Preprocess 450k and 850k methylation IDAT files in parallel using Minfi, ENmix, and meffil
• Convenient and scalable implementation
• Imputation and Feature Selection
• Preparation for machine learning pipelines

Why:

• Make DNAm accessible to python developers and more machine learning oriented researchers
• Streamlined analysis makes processing easy

PyMethyProcess is now available in Bioinformatics: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz594/5542385 .