Signal-level algorithms for MinION data

Analysis Pipeline for Single Cell ATAC-seq

Single-cell Transcriptome and Regulome Analysis Pipeline

Deep learning infrastructure for genomics

Tombo is a suite of tools primarily for the identification of modified nucleotides from raw nanopore sequencing data.

🎯 ChIP peak Annotation, Comparison and Visualization

Megalodon is a research command line tool to extract high accuracy modified base and sequence variant calls from raw nanopore reads by anchoring the information rich basecalling neural network output to a reference genome/transriptome.

Deep neural networks for predicting CpG methylation

WGBS/NOMe-seq Data Processing & Differential Methylation Analysis

Detecting methylation using signal-level features from Nanopore sequencing reads

mgatk: mitochondrial genome analysis toolkit

R package for Inference of differentially methylated regions (DMRs) from bisulfite sequencing

Haystack: Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline

Code for the paper "Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts"

Cell type specific enrichments using finemapped variants and quantitative epigenetic data

Python package to analyze DNA methylation data

Delineation of tumor cell subpopulations using MAAS

MrBiomics - Modules & Recipes augment Bioinformatics for Multi-Omics Analyses at Scale

Python-based preprocessing software for Illumina methylation arrays

A preprocessing and QC pipeline for HiChIP data