Epigenomics Tools

F-Seq2 is a Python-based peak caller for high-throughput sequencing data (ChIP-seq, DNase-seq, ATAC-seq) that uses kernel density estimation combined with a local Poisson statistical framework to identify biologically meaningful genomic regions.

Genrich is a peak-caller for genomic enrichment assays (e.g. ChIP-seq, ATAC-seq). It analyzes alignment files generated following the assay and produces a file detailing peaks of significant enrichment.

GimmeMotifs is a de novo motif prediction pipeline, especially suited for ChIP-seq datasets. It incorporates several existing motif prediction algorithms in an ensemble method to predict motifs and clusters these motifs using the WIC similarity scoring metric.

This tool was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, it can analyze data from digestion protocols as well as data from protocols that do not require restriction enzyme such as DNase Hi-C. The pipeline is flexible, scalable and optimized. It can operate either on a single laptop or on a computational cluster using the PBS-Torque scheduler.

A web server for reproducible Hi-C, capture Hi-C and single-cell Hi-C data analysis, quality control and visualization. HiCExplorer — HiCExplorer 3.6 documentation. scHiCExplorer — scHiCExplorer 7 documentation. Free document hosting provided by Read the Docs.

A mapping pipeline for HiC interaction data. Performs independent mapping on each end of the interaction pair and removes commonly found artefacts.

Jointly defining cell types from multiple single-cell datasets using LIGER. LIGER (Linked Inference of Genomic Experimental Relationships). LIGER (liger) is a package for integrating and analyzing multiple single-cell datasets, developed by the Macosko lab and maintained/extended by the Welch lab. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors.

A clustering approach for identification of enriched domains from histone modification ChIP-seq data.

SnapATAC (Single Nucleus Analysis Pipeline for ATAC-seq) is a fast, accurate and comprehensive method for analyzing single cell ATAC-seq datasets.

Fast and accurate alignment of BS-Seq reads using bwa-mem and a 3-letter genome

Epigenomics Single Cell Analysis in Python.

epic2 is an ultraperformant reimplementation of SICER. It focuses on speed, low memory overhead and ease of use. It also contains a reimplementation of the SICER-df scripts for differential enrichment and a script to create many kinds of bigwigs from your data.