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16 tools

Epigenomics Tools

Discover our collection of 16 research tools and applications for epigenomics.

Related Categories

Genomics9
ChIP-seq analysis4
Sequence analysis2
ATAC-seq analysis2
3D Genome organization2
Chromatin conformation analysis2
+13 more

Tools in Epigenomics

Found 16 of 16 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.

Tool for discovering motifs in a group of related DNA or protein sequences. A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences. This tool represents motifs as position-dependent letter-probability matrices which describe the probability of each possible letter at each position in the pattern.

Nanopolish is a software package for signal-level analysis of Oxford Nanopore sequencing data, supporting genome assembly polishing, variant calling, methylation detection, and other analyses using raw electrical signal data from the sequencer.

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.

metilene

metilene is a versatile tool to study the effect of epigenetic modifications in differentiation/development, tumorigenesis, and systems biology on a global, genome-wide level. Whether in the framework of international consortia with dozens of samples per group, or even without biological replicates, it produces highly significant and reliable results

modbam2bed is a tool for converting modified base information from BAM files (containing MM and ML tags from Oxford Nanopore sequencing) into bedMethyl format for downstream analysis of DNA methylation.