PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 31368477.
- Also identified by DOI 10.1093/bioinformatics/btz594 and PMC identifier 6954637.
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Abstract
Performing highly parallelized preprocessing of methylation array data using Python can accelerate data preparation for downstream methylation analyses, including large scale production-ready machine learning pipelines. We present a highly reproducible, scalable pipeline (PyMethylProcess) that can be quickly set-up and deployed through Docker and PIP. Project Home Page: https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess. Available on PyPI (pymethylprocess), Docker (joshualevy44/pymethylprocess). Supplementary data are available at Bioinformatics online.
Medical subject headings
- DNA Methylation
- Workflow