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FIREcaller: Detecting Frequently Interacting Regions from Hi-C Data

https://doi.org/10.1101/619288

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Compendium of Chromatin Contact Maps Reveals Spatially Active Regions in the Human Genome

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Chromatin Domains: The Unit of Chromosome Organization

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The emerging roles of TCF4 in disease and development

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The Hitchhiker’s guide to Hi-C analysis: Practical guidelines

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Common variants conferring risk of schizophrenia

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Topological domains in mammalian genomes identified by analysis of chromatin interactions

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A high-resolution map of the three-dimensional chromatin interactome in human cells

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Chromatin architecture reorganization during stem cell differentiation

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Integrative analysis of 111 reference human epigenomes

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Chromosome conformation elucidates regulatory relationships in developing human brain

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Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture

inferredcites →https://doi.org/10.1038/nmeth.3205openalex-snapshot

Fine-scale chromatin interaction maps reveal the cis-regulatory landscape of human lincRNA genes

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Deciphering non-coding variation with 3D epigenomics

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Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data

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Genome-wide mapping and analysis of chromosome architecture

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Regulation of disease-associated gene expression in the 3D genome

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Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia

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Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes

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A compendium of promoter-centered long-range chromatin interactions in the human genome

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Identifying statistically significant chromatin contacts from Hi-C data with FitHiC2

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The ENCODE Blacklist: Identification of Problematic Regions of the Genome

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Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

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A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

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HiCNorm: removing biases in Hi-C data via Poisson regression

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circlize implements and enhances circular visualization in R

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A hidden Markov random field-based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data

inferredcites →https://doi.org/10.1093/bioinformatics/btw240openalex-snapshot

FastHiC: a fast and accurate algorithm to detect long-range chromosomal interactions from Hi-C data

inferredcites →https://doi.org/10.1093/bioinformatics/btx359openalex-snapshot

HUGIn: Hi-C Unifying Genomic Interrogator

inferredcites →https://doi.org/10.1093/hmg/ddy164openalex-snapshot

Gene regulation in the 3D genome

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Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

inferredcites →https://doi.org/10.1101/406330openalex-snapshot

Using three-dimensional regulatory chromatin interactions from adult and fetal cortex to interpret genetic results for psychiatric disorders and cognitive traits

inferredcites →https://doi.org/10.1101/gr.160374.113openalex-snapshot

Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts

inferredcites →https://doi.org/10.1126/science.1181369openalex-snapshot

Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome

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Systematic mapping of functional enhancer–promoter connections with CRISPR interference

inferredcites →https://doi.org/10.1126/science.aat7615openalex-snapshot

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

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Comprehensive functional genomic resource and integrative model for the human brain

inferredcites →https://doi.org/10.1146/annurev-cellbio-100616-060531openalex-snapshot

The Three-Dimensional Organization of Mammalian Genomes

inferredcites →https://doi.org/10.1186/gb-2008-9-9-r137openalex-snapshot

Model-based Analysis of ChIP-Seq (MACS)

inferredcites →https://doi.org/10.1186/s13059-019-1658-7openalex-snapshot

Measuring the reproducibility and quality of Hi-C data

inferredcites →https://doi.org/10.1186/s13059-019-1855-4openalex-snapshot

Common DNA sequence variation influences 3-dimensional conformation of the human genome

inferredcites →https://doi.org/10.3389/fgene.2020.00158openalex-snapshot

TADCompare: An R Package for Differential and Temporal Analysis of Topologically Associated Domains

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-71881-7_13openalex-snapshot

Machine Learning and Deep Learning in Genetics and Genomics

inferred← citeshttps://doi.org/10.1016/j.jbc.2021.100581openalex-snapshot

Super hotspots and super coldspots in the repair of UV-induced DNA damage in the human genome

inferred← citeshttps://doi.org/10.1016/j.xhgg.2021.100063openalex-snapshot

From GWAS variant to function: A study of ∼148,000 variants for blood cell traits

inferred← citeshttps://doi.org/10.1101/2020.04.16.045369openalex-snapshot

Nucleotide excision repair hotspots and coldspots of UV-induced DNA damage in the human genome

inferred← citeshttps://doi.org/10.1101/2020.05.14.096917openalex-snapshot

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

inferred← citeshttps://doi.org/10.1101/2021.01.11.426176openalex-snapshot

Biop-C: A Method for Chromatin Interactome Analysis of Solid Cancer Needle Biopsy Samples

inferred← citeshttps://doi.org/10.1371/journal.pgen.1010102openalex-snapshot

THUNDER: A reference-free deconvolution method to infer cell type proportions from bulk Hi-C data

inferred← citeshttps://doi.org/10.3389/fgene.2021.673530openalex-snapshot

Profiling of 3D Genome Organization in Nasopharyngeal Cancer Needle Biopsy Patient Samples by a Modified Hi-C Approach

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