scholarly journals epiTAD: a web application for visualizing high throughput chromosome conformation capture data in the context of genetic epidemiology

2018 ◽  
Author(s):  
Jordan H. Creed ◽  
Garrick Aden-Buie ◽  
Alvaro N. Monteiro ◽  
Travis A. Gerke
Keyword(s):  
High Throughput ◽  
Genetic Epidemiology ◽  
In Silico ◽  
Web Application ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Web Based ◽  
Genome Wide ◽  
Public Data ◽  
Complex Scale

AbstractThe increasing availability of public data resources coupled with advancements in genomic technology has created greater opportunities for researchers to examine the genome on a large and complex scale. To meet the need for integrative genome wide exploration, we present epiTAD. This web-based tool enables researchers to compare genomic structures and annotations across multiple databases and platforms in an interactive manner in order to facilitate in silico discovery. epiTAD can be accessed at https://apps.gerkelab.com/epiTAD/.

scholarly journals epiTAD: a web application for visualizing chromosome conformation capture data in the context of genetic epidemiology

2019 ◽  
Vol 35 (21) ◽  
pp. 4462-4464
Author(s):  
Jordan H Creed ◽  
Garrick Aden-Buie ◽  
Alvaro N Monteiro ◽  
Travis A Gerke
Keyword(s):  
Genetic Epidemiology ◽  
In Silico ◽  
Web Application ◽  
Large Scale ◽  
Source Code ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Web Based ◽  
Genome Wide ◽  
Public Data

Abstract Summary Complementary advances in genomic technology and public data resources have created opportunities for researchers to conduct multifaceted examination of the genome on a large scale. To meet the need for integrative genome wide exploration, we present epiTAD. This web-based tool enables researchers to compare genomic 3D organization and annotations across multiple databases in an interactive manner to facilitate in silico discovery. Availability and implementation epiTAD can be accessed at https://apps.gerkelab.com/epiTAD/ where we have additionally made publicly available the source code and a Docker containerized version of the application.

scholarly journals Chromosome-Level Genome Assemblies: Expanded Capabilities for Conservation Biology Research

Proceedings ◽  
2020 ◽  
Vol 76 (1) ◽  
pp. 10
Author(s):  
Azamat Totikov ◽  
Andrey Tomarovsky ◽  
Lorena Derezanin ◽  
Olga Dudchenko ◽  
Erez Lieberman-Aiden ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
High Throughput ◽  
Conservation Biology ◽  
Threatened Species ◽  
Draft Genome ◽  
Chromosome Conformation ◽  
Genome Wide ◽  
Genome Assemblies ◽  
Biology Research ◽  
Chromosome Level

Genome assemblies are becoming increasingly important for understanding genetic diversity in threatened species. However, due to limited budgets in the area of conservation biology, genome assemblies, when available, tend to be highly fragmented with tens of thousands of scaffolds. The recent advent of high throughput chromosome conformation capture (Hi-C) makes it possible to generate more contiguous assemblies containing scaffolds that are length of entire chromosomes. Such assemblies greatly facilitate analyses and visualization of genome-wide features. We compared genetic diversity in seven threatened species that had both draft genome assemblies and newer chromosome-level assemblies available. Chromosome-level assemblies allowed better estimation of genetic diversity, localization, and, especially, visualization of low heterozygosity regions in the genomes.

scholarly journals Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data

2016 ◽  
Author(s):  
Guillaume Devailly ◽  
Anna Mantsoki ◽  
Anagha Joshi
Keyword(s):  
High Throughput ◽  
Web Application ◽  
High Throughput Sequencing ◽  
Single Gene ◽  
Public Domain ◽  
Web Tool ◽  
The Public ◽  
Link Type ◽  
A Genome ◽  
Public Data

SummaryBetter protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments (ChIP-seq, RNA-seq and CAGE) provided by a user, to the data in the public domain. Heat*seq currently contains over 12,000 experiments across diverse tissue and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualise user experiments. High quality figures and tables are produced and can be downloaded in multiple formats.AvailabilityWeb application:www.heatstarseq.roslin.ed.ac.uk/. Source code:https://github.com/[email protected];[email protected]

scholarly journals Bayesian inference of chromatin structure ensembles from population Hi-C data

2018 ◽  
Author(s):  
Simeon Carstens ◽  
Michael Nilges ◽  
Michael Habeck
Keyword(s):  
Bayesian Inference ◽  
High Throughput ◽  
Chromatin Structure ◽  
Genomic Structure ◽  
Large Population ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Cell To Cell Variability ◽  
Rigorous Method

High-throughput chromosome conformation capture (Hi-C) experiments are typically performed on a large population of cells and therefore only yield average numbers of genomic contacts. Nevertheless population Hi-C data are often interpreted in terms of a single genomic structure, which ignores all cell-to-cell variability. We propose a probabilistic, statistically rigorous method to infer chromatin structure ensembles from population Hi-C data that takes the ensemble nature of the data explicitly into account and allows us to infer the number of structures required to explain the data.

scholarly journals No kissing in the nucleus: Unbiased analysis reveals no evidence of trans chromosomal regulation of mammalian immune development

2017 ◽  
Author(s):  
Timothy M. Johanson ◽  
Hannah D. Coughlan ◽  
Aaron T.L. Lun ◽  
Naiara G. Bediaga ◽  
Gaetano Naselli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Immune Cells ◽  
Chromosome Conformation Capture ◽  
Chromosome Conformation ◽  
Immune Development ◽  
Regulate Gene Expression ◽  
Genome Wide ◽  
Capture Technique ◽  
Regulate Gene

SummaryIt has been proposed that interactions between mammalian chromosomes, or transchromosomal interactions (also known as kissing chromosomes), regulate gene expression and cell fate determination. Here we aimed to identify novel transchromosomal interactions in immune cells by high-resolution genome-wide chromosome conformation capture. Although we readily identified stable interactions in cis, and also between centromeres and telomeres on different chromosomes, surprisingly we identified no gene regulatory transchromosomal interactions in either mouse or human cells, including previously described interactions. We suggest that advances in the chromosome conformation capture technique and the unbiased nature of this approach allow more reliable capture of interactions between chromosomes than previous methods. Overall our findings suggest that stable transchromosomal interactions that regulate gene expression are not present in mammalian immune cells and that lineage identity is governed by cis, not trans chromosomal interactions.

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