Aims to map global open chromatin interactions. OCEAN-C is a program allowing users to study open chromatin interactions and their relationship with gene regulation. This tool is developed for capturing interactions between open chromatin regions without relying on specific antibodies. It includes features for investigating changes in open chromatin conformations, such as promoter-enhancer interactions, that result in differential gene expression.
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Allows users to analyze how pathways and genetic interactions rewire over time. MODIFI identifies and characterizes differential interactions. This two-factor linear model can estimate the predictive strength and influence of time and differential compound treatment on pi-score. This estimation can be described as the slope by which an interaction changes (strengthens or weakens) over time.
A web-based application for visualizing, annotating, and querying chromatin interactions derived from technologies such as ChIA-PET or HiC. QuIN enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.
Integrates existing pipelines focusing on individual steps of Hi-C data processing into an all-in-one package with adjustable parameters to infer the consensus 3D structure of genome from raw Hi-C sequencing data. HBP could assign statistical confidence estimation for chromatin interactions, and clustering interaction loci according to enrichment tracks or topological structure automatically. HBP provides the tools for the sequence mapping of raw reads, extraction and normalization of chromosome interactions, heatmap visualization of interaction frequency, network analysis of specific interactions, statistical evaluation with adjustable parameters.
Permits users to find differential chromatin interactions between two Hi-C contact maps. SELFISH can make interactions in a robust way by using self-similitary.
Exploits sequence features and epigenomic data to forecast chromatin contacts. DeepTACT is a model which is able to perform its predictions at individual regulatory element level for determining both promoter-enhancer interactions and promoter-promoter interactions. This program assists users in investigating human disease functioning by highlighting set of hub promoters or associations for coronary artery disease.
Detects overlapping heterogeneous interactome modules (HIMs) in heterogeneous networks. MOCHI proposes a method able to consider two types of different interactomes: (i) a network of chromosomal interactions between different gene loci, and (2) a gene regulatory network (GRN) where transcription factor (TF) proteins bind to the genomic loci to regulate target genes. This approach was tested on five different human cell types.