Signal-level algorithms for MinION data
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Updated
Aug 5, 2023 - C
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
A preprocessing and QC pipeline for HiChIP data
Python-based preprocessing software for Illumina methylation arrays
Bead-based single-cell atac processing
This program analyzes methylation levels at six CpG sites in the genome of blood cells to produce a prediction of an individual's biological age, using different machine learning and deep learning models.
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