scholarly journals Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 950 ◽  
Author(s):  
Aaron T. L. Lun ◽  
Malcolm Perry ◽  
Elizabeth Ing-Simmons
Keyword(s):  
Experimental Data ◽  
Open Source ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Careful Analysis ◽  
Chromatin Conformation ◽  
Interaction Data ◽  
Genome Wide ◽  
Bioconductor Project ◽  
Basic Infrastructure

The study of genomic interactions has been greatly facilitated by techniques such as chromatin conformation capture with high-throughput sequencing (Hi-C). These genome-wide experiments generate large amounts of data that require careful analysis to obtain useful biological conclusions. However, development of the appropriate software tools is hindered by the lack of basic infrastructure to represent and manipulate genomic interaction data. Here, we present the InteractionSet package that provides classes to represent genomic interactions and store their associated experimental data, along with the methods required for low-level manipulation and processing of those classes. The InteractionSet package exploits existing infrastructure in the open-source Bioconductor project, while in turn being used by Bioconductor packages designed for higher-level analyses. For new packages, use of the functionality in InteractionSet will simplify development, allow access to more features and improve interoperability between packages.

scholarly journals Infrastructure for genomic interactions: Bioconductor classes for Hi-C, ChIA-PET and related experiments

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 950 ◽  
Author(s):  
Aaron T. L. Lun ◽  
Malcolm Perry ◽  
Elizabeth Ing-Simmons
Keyword(s):  
Experimental Data ◽  
Open Source ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Careful Analysis ◽  
Chromatin Conformation ◽  
Interaction Data ◽  
Genome Wide ◽  
Bioconductor Project ◽  
Basic Infrastructure

The study of genomic interactions has been greatly facilitated by techniques such as chromatin conformation capture with high-throughput sequencing (Hi-C). These genome-wide experiments generate large amounts of data that require careful analysis to obtain useful biological conclusions. However, development of the appropriate software tools is hindered by the lack of basic infrastructure to represent and manipulate genomic interaction data. Here, we present the InteractionSet package that provides classes to represent genomic interactions and store their associated experimental data, along with the methods required for low-level manipulation and processing of those classes. The InteractionSet package exploits existing infrastructure in the open-source Bioconductor project, while in turn being used by Bioconductor packages designed for higher-level analyses. For new packages, use of the functionality in InteractionSet will simplify development, allow access to more features and improve interoperability between packages.

scholarly journals Hi-Cpipe: a pipeline for high-throughput chromosome capture

2015 ◽  
Author(s):  
Giancarlo Castellano ◽  
François Le Dily ◽  
Antonio Hermoso Pulido ◽  
Miguel Beato ◽  
Guglielmo Roma
Keyword(s):  
High Throughput ◽  
Visual Inspection ◽  
Automated Analysis ◽  
Chromatin Conformation ◽  
Interaction Data ◽  
Alignment Quality ◽  
Bioinformatics Pipeline ◽  
Chromatin Interactions ◽  
Genome Wide ◽  
Analysis Workflow

Hi-Cpipe is a bioinformatics pipeline for the automated analysis of data generated by high-throughput chromatin conformation capture (HiC). The analysis workflow comprises steps of data formatting, genome alignment, quality control and filtering, identification of genome-wide chromatin interactions, visualization and statistics. An interactive browser enables visual inspection of interaction data and results.

scholarly journals PRIME-3D2D is a 3D2D model to predict binding sites of protein–RNA interaction

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Juan Xie ◽  
Jinfang Zheng ◽  
Xu Hong ◽  
Xiaoxue Tong ◽  
Shiyong Liu
Keyword(s):  
Full Advantage ◽  
High Throughput ◽  
Binding Sites ◽  
High Throughput Sequencing ◽  
Secondary Structures ◽  
Biological Processes ◽  
Genome Wide ◽  
Rna Interaction ◽  
Rna Complexes ◽  
Better Than

AbstractProtein-RNA interaction participates in many biological processes. So, studying protein–RNA interaction can help us to understand the function of protein and RNA. Although the protein–RNA 3D3D model, like PRIME, was useful in building 3D structural complexes, it can’t be used genome-wide, due to lacking RNA 3D structures. To take full advantage of RNA secondary structures revealed from high-throughput sequencing, we present PRIME-3D2D to predict binding sites of protein–RNA interaction. PRIME-3D2D is almost as good as PRIME at modeling protein–RNA complexes. PRIME-3D2D can be used to predict binding sites on PDB data (MCC = 0.75/0.70 for binding sites in protein/RNA) and transcription-wide (MCC = 0.285 for binding sites in RNA). Testing on PDB and yeast transcription-wide data show that PRIME-3D2D performs better than other binding sites predictor. So, PRIME-3D2D can be used to predict the binding sites both on PDB and genome-wide, and it’s freely available.

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.

Genome-wide identification of low phosphorus responsive microRNAs in two soybean genotypes by high-throughput sequencing

2020 ◽  
Vol 20 (6) ◽  
pp. 825-838
Author(s):  
Xiaoqian Liu ◽  
Shanshan Chu ◽  
Chongyuan Sun ◽  
Huanqing Xu ◽  
Jinyu Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Genome Wide ◽  
Low Phosphorus ◽  
Soybean Genotypes
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