PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.
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ABSTRACT:
SUBMITTER: Levy JJ
PROVIDER: S-EPMC6954637 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Publications
PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.
Levy Joshua J JJ Titus Alexander J AJ Salas Lucas A LA Christensen Brock C BC
Bioinformatics (Oxford, England) 20191201 24
<h4>Summary</h4>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.<h4>Availability and implementation</h4>Project Home Page: https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess. Available ...[more]
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