scholarly journals IDR2D identifies reproducible genomic interactions

2019 ◽  
Author(s):  
Konstantin Krismer ◽  
Yuchun Guo ◽  
David K. Gifford
Keyword(s):  
Gene Regulation ◽  
Genome Organization ◽  
Genome Biology ◽  
Chromatin Interaction ◽  
Interaction Data ◽  
Bioconductor Package ◽  
Online Service ◽  
Link Type

AbstractChromatin interaction data from protocols such as ChIA-PET, HiChIP, and HiC provide valuable insights into genome organization and gene regulation, but can include spurious interactions that do not reflect underlying genome biology. We introduce a generalization of the Irreproducible Discovery Rate (IDR) method called IDR2D that identifies replicable interactions shared by chromatin interaction experiments. IDR2D provides a principled set of interactions and eliminates artifacts from single experiments. The method is available as a Bioconductor package for the R community, as well as an online service at https://idr2d.mit.edu.

scholarly journals IDR2D identifies reproducible genomic interactions

2020 ◽  
Vol 48 (6) ◽  
pp. e31-e31
Author(s):  
Konstantin Krismer ◽  
Yuchun Guo ◽  
David K Gifford
Keyword(s):  
Gene Regulation ◽  
Genome Organization ◽  
Genome Biology ◽  
Chromatin Interaction ◽  
Interaction Data ◽  
Bioconductor Package ◽  
Online Service

Abstract Chromatin interaction data from protocols such as ChIA-PET, HiChIP and Hi-C provide valuable insights into genome organization and gene regulation, but can include spurious interactions that do not reflect underlying genome biology. We introduce an extension of the Irreproducible Discovery Rate (IDR) method called IDR2D that identifies replicable interactions shared by chromatin interaction experiments. IDR2D provides a principled set of interactions and eliminates artifacts from single experiments. The method is available as a Bioconductor package for the R community, as well as an online service at https://idr2d.mit.edu.

scholarly journals The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions

2017 ◽  
Author(s):  
Yanli Wang ◽  
Bo Zhang ◽  
Lijun Zhang ◽  
Lin An ◽  
Jie Xu ◽  
...  
Keyword(s):  
Genome Organization ◽  
Target Genes ◽  
Genome Structure ◽  
Regulatory Elements ◽  
Genomic Region ◽  
Genome Browser ◽  
Chromatin Interaction ◽  
Interaction Data ◽  
3D Genome ◽  
Chromatin Interactions

ABSTRACTRecent advent of 3C-based technologies such as Hi-C and ChIA-PET provides us an opportunity to explore chromatin interactions and 3D genome organization in an unprecedented scale and resolution. However, it remains a challenge to visualize chromatin interaction data due to its size and complexity. Here, we introduce the 3D Genome Browser (http://3dgenome.org), which allows users to conveniently explore both publicly available and their own chromatin interaction data. Users can also seamlessly integrate other “omics” data sets, such as ChIP-Seq and RNA-Seq for the same genomic region, to gain a complete view of both regulatory landscape and 3D genome structure for any given gene. Finally, our browser provides multiple methods to link distal cis-regulatory elements with their potential target genes, including virtual 4C, ChIA-PET, Capture Hi-C and cross-cell-type correlation of proximal and distal DNA hypersensitive sites, and therefore represents a valuable resource for the study of gene regulation in mammalian genomes.

scholarly journals Probing multi-way chromatin interaction with hypergraph representation learning

2020 ◽  
Author(s):  
Ruochi Zhang ◽  
Jian Ma
Keyword(s):  
Genome Organization ◽  
Representation Learning ◽  
Higher Order ◽  
Computational Method ◽  
Chromatin Interaction ◽  
Interaction Data ◽  
3D Genome ◽  
Chromatin Interactions ◽  
Single Nucleus ◽  
And Function

AbstractAdvances in high-throughput mapping of 3D genome organization have enabled genome-wide characterization of chromatin interactions. However, proximity ligation based mapping approaches for pairwise chromatin interaction such as Hi-C cannot capture multi-way interactions, which are informative to delineate higher-order genome organization and gene regulation mechanisms at single-nucleus resolution. The very recent development of ligation-free chromatin interaction mapping methods such as SPRITE and ChIA-Drop has offered new opportunities to uncover simultaneous interactions involving multiple genomic loci within the same nuclei. Unfortunately, methods for analyzing multi-way chromatin interaction data are significantly underexplored. Here we develop a new computational method, called MATCHA, based on hypergraph representation learning where multi-way chromatin interactions are represented as hyperedges. Applications to SPRITE and ChIA-Drop data suggest that MATCHA is effective to denoise the data and make de novo predictions of multi-way chromatin interactions, reducing the potential false positives and false negatives from the original data. We also show that MATCHA is able to distinguish between multi-way interaction in a single nucleus and combination of pairwise interactions in a cell population. In addition, the embeddings from MATCHA reflect 3D genome spatial localization and function. MATCHA provides a promising framework to significantly improve the analysis of multi-way chromatin interaction data and has the potential to offer unique insights into higher-order chromosome organization and function.

scholarly journals GenomicInteractions: An R/Bioconductor package for manipulating and investigating chromatin interaction data

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Nathan Harmston ◽  
Elizabeth Ing-Simmons ◽  
Malcolm Perry ◽  
Anja Barešić ◽  
Boris Lenhard
Keyword(s):  
Chromatin Interaction ◽  
Interaction Data ◽  
Bioconductor Package

scholarly journals Genome organization and molecular characterization of the three Formica exsecta viruses—FeV1, FeV2 and FeV4

PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e6216 ◽  
Author(s):  
Kishor Dhaygude ◽  
Helena Johansson ◽  
Jonna Kulmuni ◽  
Liselotte Sundström
Keyword(s):  
Molecular Characterization ◽  
Genome Organization ◽  
Rna Virus ◽  
Open Reading Frames ◽  
Link Type ◽  
Infection Pathways ◽  
Comparative Genomics Analysis ◽  
First Time ◽  
Negative Sense

We present the genome organization and molecular characterization of the three Formica exsecta viruses, along with ORF predictions, and functional annotation of genes. The Formica exsecta virus-4 (FeV4; GenBank ID: MF287670) is a newly discovered negative-sense single-stranded RNA virus representing the first identified member of order Mononegavirales in ants, whereas the Formica exsecta virus-1 (FeV1; GenBank ID: KF500001), and the Formica exsecta virus-2 (FeV2; GenBank ID: KF500002) are positive single-stranded RNA viruses initially identified (but not characterized) in our earlier study. The new virus FeV4 was found by re-analyzing data from a study published earlier. The Formica exsecta virus-4 genome is 9,866 bp in size, with an overall G + C content of 44.92%, and containing five predicted open reading frames (ORFs). Our bioinformatics analysis indicates that gaps are absent and the ORFs are complete, which based on our comparative genomics analysis suggests that the genomes are complete. Following the characterization, we validate virus infection for FeV1, FeV2 and FeV4 for the first time in field-collected worker ants. Some colonies were infected by multiple viruses, and the viruses were observed to infect all castes, and multiple life stages of workers and queens. Finally, highly similar viruses were expressed in adult workers and queens of six other Formica species: F. fusca, F. pressilabris, F. pratensis, F. aquilonia, F. truncorum and F. cinerea. This research indicates that viruses can be shared between ant species, but further studies on viral transmission are needed to understand viral infection pathways.

scholarly journals XlinkCyNET: a Cytoscape application for visualization of protein interaction networks based on cross-linking mass-spectrometry identifications

2020 ◽  
Author(s):  
Diogo Borges Lima ◽  
Ying Zhu ◽  
Fan Liu
Keyword(s):  
Mass Spectrometry ◽  
Protein Interaction ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Cross Linking ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Link Type

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.

scholarly journals OnTAD: hierarchical domain structure reveals the divergence of activity among TADs and boundaries

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Lin An ◽  
Tao Yang ◽  
Jiahao Yang ◽  
Johannes Nuebler ◽  
Guanjue Xiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Domain Structure ◽  
High Frequency ◽  
Spatial Organization ◽  
Structural Units ◽  
Regulatory Interactions ◽  
Link Type ◽  
Topologically Associating Domains

AbstractThe spatial organization of chromatin in the nucleus has been implicated in regulating gene expression. Maps of high-frequency interactions between different segments of chromatin have revealed topologically associating domains (TADs), within which most of the regulatory interactions are thought to occur. TADs are not homogeneous structural units but appear to be organized into a hierarchy. We present OnTAD, an optimized nested TAD caller from Hi-C data, to identify hierarchical TADs. OnTAD reveals new biological insights into the role of different TAD levels, boundary usage in gene regulation, the loop extrusion model, and compartmental domains. OnTAD is available at https://github.com/anlin00007/OnTAD.

scholarly journals Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Haitham Ashoor ◽  
Xiaowen Chen ◽  
Wojciech Rosikiewicz ◽  
Jiahui Wang ◽  
Albert Cheng ◽  
...  
Keyword(s):  
Unsupervised Learning ◽  
Graph Embedding ◽  
Chromatin Interaction ◽  
Interaction Data

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

2013 ◽  
Vol 14 (6) ◽  
pp. 390-403 ◽  
Author(s):  
Job Dekker ◽  
Marc A. Marti-Renom ◽  
Leonid A. Mirny
Keyword(s):  
Three Dimensional ◽  
Chromatin Interaction ◽  
Interaction Data

scholarly journals DNA Rchitect: an R based visualizer for network analysis of chromatin interaction data

2019 ◽  
Author(s):  
R N Ramirez ◽  
K Bedirian ◽  
S M Gray ◽  
A Diallo
Keyword(s):  
Open Source ◽  
Web Application ◽  
Genomic Data ◽  
Chromatin Interaction ◽  
Chromatin Conformation ◽  
Interaction Data ◽  
Data Types ◽  
Network Analyses ◽  
Interactive Network ◽  
Network Functionality

Abstract Motivation Visualization of multiple genomic data generally requires the use of public or commercially hosted browsers. Flexible visualization of chromatin interaction data as genomic features and network components offer informative insights to gene expression. An open source application for visualizing HiC and chromatin conformation-based data as 2D-arcs accompanied by interactive network analyses is valuable. Results DNA Rchitect is a new tool created to visualize HiC and chromatin conformation-based contacts at high (Kb) and low (Mb) genomic resolutions. The user can upload their pre-filtered HiC experiment in bedpe format to the DNA Rchitect web app that we have hosted or to a version they themselves have deployed. Using DNA Rchitect, the uploaded data allows the user to visualize different interactions of their sample, perform simple network analyses, while also offering visualization of other genomic data types. The user can then download their results for additional network functionality offered in network based programs such as Cytoscape. Availability and implementation DNA Rchitect is freely available both as a web application written primarily in R available at http://shiny.immgen.org/DNARchitect/ and as an open source released under an MIT license at: https://github.com/alosdiallo/DNA_Rchitect.

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