Pylluminator: fast and scalable analysis of DNA methylation data in Python

Motivation Illumina Infinium BeadChip technology for DNA methylation analysis continues to expand, with the latest EPICv2 arrays targeting about a million loci. As data volumes from this technology continue to grow, there is increasing demand for more scalable data processing solutions. Meanwhile, Python has gained significant interest in bioinformatics for its efficiency, versatility, and widespread use in data science and machine learning. Yet, no comprehensive Python toolkit exists for Illumina methylation array analysis.

We present Pylluminator, a Python implementation of essential analysis methods including pre-processing tools, quality control, differential methylation analysis, and visualizations. Based on the established R packages SeSAMe and ChAMP, Pylluminator provides a scalable, user-friendly toolkit for DNA methylation analysis. Availability and implementation Pylluminator is an open-source package under MIT license available at https://github.com/eliopato/pylluminator. It was developed using Python 3.12 and can be installed with pip. The documentation with thorough installation instructions and examples can be found at https://pylluminator.readthedocs.io Competing Interest Statement The authors have declared no competing interest. Abbreviations - BAMS - Bosma Arhinia Microphthalmia Syndrome - CNS - Copy Number Segmentation - CNV - Copy Number Variation - DMP - Differentially Methylated Probe - DMR - Differentially Methylated Region - FSHD1 Type 1 - FacioScapuloHumeral muscular Dystrophy - FSHD2 Type 2 - FacioScapuloHumeral muscular Dystrophy - LMM - Linear Mixed model - NOOB - Normal-exponential Out-Of-Band - OLS - Ordinary Least Squares - pOOBAH - p-values Out-Of-Band Array Hybridization