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

MrBiomics: Modules & Recipes augment Bioinformatics for Multi-Omics Analyses

Python package to analyze DNA methylation data

Delineation of tumor cell subpopulations using MAAS

A preprocessing and QC pipeline for HiChIP data

Python-based preprocessing software for Illumina methylation arrays