HiCExplorer is a powerful and easy to use set of tools to process, normalize and visualize Hi-C data.
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Updated
Oct 1, 2024 - Python
HiCExplorer is a powerful and easy to use set of tools to process, normalize and visualize Hi-C data.
3DGB is a workflow to build 3D models of genomes from HiC data
FIREcaller: Python library for detecting Frequently Interacting REgions (FIREs) from Hi-C data
Snakemake wrapper around the Arima Capture Hi-C (CHiC) workflow
Configurable Hi-C pipeline that is easy to use
a Snakemake version of distiller - the Open2C Hi-C mapping workflow
Snakemake pipeline for analysis and normalization of Hi-C data starting from fastq.gz files. It includes the possibility to perform grouped analyses, TAD, loops and stripes detections, as well as differential compartment and chromatin interaction analyses.
A two-step model that combines neural network and ensemble learning to predict OCR–mediated interactions.
A python library to display HiC data on a circular strip and to integrate genomic data
Snakemake workflow for processing Arima HIC data
Hi-C Architect for Neural Networks
Make a phylogeny using the chromatin structure information extracted from Hi-C experiments (mirror of the original repo)
HiC sunt dracones - or HiCDS in short - Your little helper for the HiC analysis
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