ArticleBriefings in bioinformatics2025
AutoMethyc: an automated methylation analysis for massively parallel sequencing data.
Article in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
Funding
Abstract
motivationBisulfite sequencing (BS-Seq) enables a comprehensive and detailed analysis of DNA methylation patterns at single-nucleotide resolution. While methylation differences can contribute to various diseases, their sincronous occurrence at distinct loci complicates understanding. Therefore, advanced tools are essential to facilitate the identification and analysis of methylation programs and patterns.
resultsAutoMethyc provides a comparative approach by integrating different algorithms coordinated and optimized for use on desktop computers and servers. The workflow evaluates the methylation status from different perspectives, facilitating interpretation in an interactive HTML report, incorporating new co-methylation analyses for marker identification, as well as exploratory complex workflows with dimension reduction techniques and identification of unsupervised groups between samples or sites. AutoMethyc was tested in a breast cancer study ($n=389$; 233 cases and 156 controls) using BS-Seq data from the Illumina MiSeq platform, mapping 330 methylation-prone citocine (CpG) sites in 20 genes. The analysis was performed on a desktop with 64 GB RAM, 16 cores (4.673 GHz), and 326 KB/s internet, running Fedora 39 with i3wm. The tool processed the dataset in 48 h, showcasing its efficiency and scalability.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.