A collection of resources to filter 'bad' probes from the Illumina 450k and EPIC methylation arrays

Bayesian modelling of DNA methylation heterogeneity at single-cell resolution

Python toolkit for parsing, processing, and analysis of Illumina methylation array IDAT files

Comprehensive tool for visualizing genome-wide cytosine data.

A methylation array analysis pipeline tailored for discovering rare methylation events with interactive data visualization

Regional Association of Methylation variability with the Exposome and geNome (RAMEN) is an R package whose goal is to identify Variable Methylated Regions (VMRs) in microarray DNA methylation data. Additionally, using Genotype (G) and Environmental (E) data, it can identify which G, E, G+E or GxE model better explains this variability.

This package provides Illumina Mouse Methylation Array Annotation (12.v1, Genome Build mm10) compatible with minfi.

This package provides Illumina Mouse Methylation Array Manifest (12.v1, Genome Build mm10) compatible with minfi.

adaptable and intrepretable,multi-task learning based gene-level methylation estimations

Impact of lossy compression of nanopore raw signal data on basecall and consensus accuracy

DNA methylation analysis pipeline for reduced representation bissulfite sequencing data

Re-implementation of J. Beaulaurier et al's SMSN strategy, using the default PacBio tools

The transferase system for retrieving methylome data from methbase

Fast and efficient conversion of Nanopore modBAM from guppy basecaller to BED files for differential methylation and machine learning predictions

Practical and home works in the discipline Bioinformatics.

MultiNano is a deep learning framework designed for predicting m6A RNA modifications using raw electrical signals from Oxford Nanopore sequencing. It provides high accuracy across species and conditions, offering a user-friendly pipeline for researchers. MultiNano supports both training from scratch and direct prediction modes.

Differentially methylated regions analysis

The following repository contains code to analyse MeD-seq data and detect statistically significant genomic bins.

Workflow and scripts for analyzing Illumina MethylationEPIC v2.0 array data using the sesame R package.

A repository containing code, data, and resource links for the publication "Characterization of universal features of partially methylated domains across tissues and species"