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.

scholarly journals Chromatin interaction data visualization in the WashU Epigenome Browser

2017 ◽  
Author(s):  
Daofeng Li ◽  
Silas Hsu ◽  
Deepak Purushotham ◽  
Ting Wang
Keyword(s):  
Data Visualization ◽  
Chromatin Interaction ◽  
Chromatin Conformation ◽  
Interaction Data ◽  
Computational Resource ◽  
Genome Maintenance ◽  
Data Format ◽  
Chromatin Interactions ◽  
Data Formats ◽  
Gene Regulations

AbstractMotivationLong-range chromatin interactions are critical for gene regulations and genome maintenance. HiC and Cool are the two most common data formats used by the community, including the 4D Nucleome Consortium (4DN), to represent chromatin interaction data from a variety of chromatin conformation capture experiments, and specialized tools were developed for their analysis, visualization, and conversion. However, there does not exist a tool that can support visualization of both data formats simultaneously.ResultsThe WashU Epigenome Browser has integrated both HiC and Cool data formats into its visualization platform. Investigators can seamlessly explore chromatin interaction data regardless of their underlying data format. For developers it is straightforward to benchmark the differences in rendering speed and computational resource usage between the two data formats.Availabilityhttp://epigenomegateway.wustl.edu/browser/.

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.

Borehole Data Management System: a web interface for borehole data acquisition

2020 ◽  
Author(s):  
Massimiliano Cannata ◽  
Milan Antonovic ◽  
Nils Oesterling ◽  
Sabine Brodhag
Keyword(s):  
Data Management ◽  
Open Source ◽  
Management System ◽  
Web Application ◽  
Data Management System ◽  
Data Types ◽  
Time Data ◽  
Borehole Data ◽  
Geological Conditions ◽  
Combining Data

<p>The shallow underground is of primary importance in governing and planning the territories where we live. In fact, the uppermost 500 meters below the ground surface are interested by a growing number of anthropic activities like constructions, extraction of drinking water, mineral resources, installation of geothermal probes, etc. Borehole data are therefore essential as they reveal at specific location the vertical sequence of geological layers which in turns can provide an understanding of the geological conditions we can expect in the shallow underground. Unfortunately, data are rarely available in a <em>FAIR way</em> that as the acronym specify are Findable, Accessible, Interoperable and Reusable.</p><p>Most of the time data, particularly those collected in the past, are in the form of <strong>static data reports</strong> that describe the stratigraphy and the related characteristics; these data types are generally available as paper documents, or static files like .pdf of images (.ai). While very informative, these documents are not searchable, not interoperable nor easily reusable, since they require a non negligible time for data integration. Sometime, <strong>data are archived into database</strong>. This certainly improve the find-ability of the data and its accessibility but still do not address the interoperability requirement and therefore, combining data from different sources remain a problematic task. To enable FAIR borehole data and facilitate the different entities (public or private) management swisstopo (www.swisstopo.ch) has funded the development of a Web application named Borehole Data Management System (BDMS) [1] that adopt the <strong>borehole data model</strong> () [2] implemented by the Swiss Geological Survey.</p><p>Among the benefits of adopting a standard model we can identify:</p><ul><li>Enhance the exchange, the usage and quality of the data</li> <li>Reach data harmonization (level of detail, precise definitions, relationships and dependencies among the data),</li> <li>Establish a common language between stakeholders</li> </ul><p>The Borehole Data Management System (BDMS)  was developed using the latest Free and Open Source Technologies. The new application integrates some of the today’s best OSGeo projects and is available as a modular open source solution on GitHub and ready to use in a docker container available on Docker Hub. Through two types of authorization, <em>Explorer </em>users are able to search the BDMS for specific boreholes, navigate a configurable user friendly map, apply filters, explore the stratigraphy layers of each borehole and export all the data in Shapefiles, CSV or PDF. <em>Editors</em> are able to manage in details the informations and publish the results after passing a validation process.</p><p> </p><p>Links</p><p>[1] http://geoservice.ist.supsi.ch/docs/bdms/index.html</p><p>[2] https://www.geologieportal.ch/en/knowledge/lookup/data-models/borehole-data-model.html </p>

An open-source R-package and web application for high-quality probabilistic predictions in hydrology

2021 ◽  
Author(s):  
Jason Hunter ◽  
Mark Thyer ◽  
Dmitri Kavetski ◽  
David McInerney
Keyword(s):  
Open Source ◽  
Web Application ◽  
R Package ◽  
Error Model ◽  
Objective Functions ◽  
High Quality ◽  
Wide Range ◽  
Probabilistic Error

<p>Probabilistic predictions provide crucial information regarding the uncertainty of hydrological predictions, which are a key input for risk-based decision-making. However, they are often excluded from hydrological modelling applications because suitable probabilistic error models can be both challenging to construct and interpret, and the quality of results are often reliant on the objective function used to calibrate the hydrological model.</p><p>We present an open-source R-package and an online web application that achieves the following two aims. Firstly, these resources are easy-to-use and accessible, so that users need not have specialised knowledge in probabilistic modelling to apply them. Secondly, the probabilistic error model that we describe provides high-quality probabilistic predictions for a wide range of commonly-used hydrological objective functions, which it is only able to do by including a new innovation that resolves a long-standing issue relating to model assumptions that previously prevented this broad application.  </p><p>We demonstrate our methods by comparing our new probabilistic error model with an existing reference error model in an empirical case study that uses 54 perennial Australian catchments, the hydrological model GR4J, 8 common objective functions and 4 performance metrics (reliability, precision, volumetric bias and errors in the flow duration curve). The existing reference error model introduces additional flow dependencies into the residual error structure when it is used with most of the study objective functions, which in turn leads to poor-quality probabilistic predictions. In contrast, the new probabilistic error model achieves high-quality probabilistic predictions for all objective functions used in this case study.</p><p>The new probabilistic error model and the open-source software and web application aims to facilitate the adoption of probabilistic predictions in the hydrological modelling community, and to improve the quality of predictions and decisions that are made using those predictions. In particular, our methods can be used to achieve high-quality probabilistic predictions from hydrological models that are calibrated with a wide range of common objective functions.</p>

MarkUs: An Open-Source Web Application to Annotate Student Papers On-Line

2012 ◽  
Author(s):  
Morgan Magnin ◽  
Guillaume Moreau ◽  
Nelle Varoquaux ◽  
Benjamin Vialle ◽  
Karen Reid ◽  
...  
Keyword(s):  
Higher Education ◽  
Open Source ◽  
Web Application ◽  
Online System ◽  
Important Benefit ◽  
Special Cases ◽  
Assessment Time ◽  
On Line ◽  
Active Pedagogy ◽  
Further Development

A critical component of the learning process lies in the feedback that students receive on their work that validates their progress, identifies flaws in their thinking, and identifies skills that still need to be learned. Many higher-education institutions have developed an active pedagogy that gives students opportunities for different forms of assessment and feedback. This means that students have numerous lab exercises, assignments, and projects. Both instructors and students thus require effective tools to efficiently manage the submission, assessment, and individualized feedback of students’ work. The open-source web application MarkUs aims at meeting these needs: it facilitates the submission and assessment of students’ work. Students directly submit their work using MarkUs, rather than printing it, or sending it by email. The instructors or teaching assistants use MarkUs’s interface to view the students’ work, annotate it, and fill in a marking rubric. Students use the same interface to read the annotations and learn from the assessment. Managing the students’ submissions and the instructors assessments within a single online system, has led to several positive pedagogical outcomes: the number of late submissions has decreased, the assessment time has been drastically reduced, students can access their results and read the instructor’s feedback immediately after the grading process is completed. Using MarkUs has also significantly reduced the time that instructors spend collecting assignments, creating the marking schemes, passing them on to graders, handling special cases, and returning work to the students. In this paper, we introduce MarkUs’ features, and illustrate their benefits for higher education through our own teaching experiences and that of our colleagues. We also describe an important benefit of the fact that the tool itself is open-source. MarkUs has been developed entirely by students giving them a valuable learning opportunity as they work on a large software system that real users depend on. Virtuous circles indeed arise, with former users of MarkUs becoming developers and then supervisors of further development. We will conclude by drawing perspectives about forthcoming features and use, both technically and pedagogically.

scholarly journals An Open-Source Web-Based Tool for Resource-Agnostic Interactive Translation Prediction

2014 ◽  
Vol 102 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Torregrosa Daniel ◽  
Forcada Mikel L. ◽  
Pérez-Ortiz Juan Antonio
Keyword(s):  
Open Source ◽  
Machine Translation ◽  
Web Application ◽  
Statistical Machine Translation ◽  
Black Box ◽  
Translation System ◽  
Web Tool ◽  
Web Based ◽  
Strongly Coupled ◽  
Machine Translation System

Abstract We present a web-based open-source tool for interactive translation prediction (ITP) and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.

scholarly journals Nextstrain: real-time tracking of pathogen evolution

2017 ◽  
Author(s):  
James Hadfield ◽  
Colin Megill ◽  
Sidney M. Bell ◽  
John Huddleston ◽  
Barney Potter ◽  
...  
Keyword(s):  
Public Health ◽  
Real Time ◽  
Web Application ◽  
Sequence Data ◽  
Data Types ◽  
Bioinformatics Pipeline ◽  
Public Health Importance ◽  
Viral Genomes ◽  
Effective Public Health ◽  
Interactive Visualisation

AbstractSummaryUnderstanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualisation platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, publicly available for use by health professionals, epidemiologists, virologists and the public alike.Availability and implementationAll code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.

scholarly journals LandScape: a web application for interactive genomic summary visualization

2019 ◽  
Author(s):  
Wenlong Jia ◽  
Hechen Li ◽  
Shiying Li ◽  
Shuaicheng Li
Keyword(s):  
Genetic Information ◽  
Web Application ◽  
Genomic Research ◽  
File Format ◽  
Data Types ◽  
Web Based ◽  
Link Type ◽  
Level Data ◽  
Real Time Visualization ◽  
Information Landscape

ABSTRACTSummaryVisualizing integrated-level data from genomic research remains a challenge, as it requires sufficient coding skills and experience. Here, we present LandScapeoviz, a web-based application for interactive and real-time visualization of summarized genetic information. LandScape utilizes a well-designed file format that is capable of handling various data types, and offers a series of built-in functions to customize the appearance, explore results, and export high-quality diagrams that are available for publication.Availability and implementationLandScape is deployed at bio.oviz.org/demo-project/analyses/landscape for online use. Documentation and demo data are freely available on this website and GitHub (github.com/Nobel-Justin/Oviz-Bio-demo)[email protected]

scholarly journals Functional annotation of human long noncoding RNAs using chromatin conformation data

2021 ◽  
Author(s):  
Saumya Agrawal ◽  
Tanvir Alam ◽  
Masaru Koido ◽  
Ivan V. Kulakovskiy ◽  
Jessica Severin ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Rna Binding ◽  
Functional Characterization ◽  
Cell Types ◽  
Chromatin Interaction ◽  
Spatial Proximity ◽  
Chromatin Conformation ◽  
Cell Type ◽  
Cell Type Specific ◽  
Rna Domains

AbstractTranscription of the human genome yields mostly long non-coding RNAs (lncRNAs). Systematic functional annotation of lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. Currently, 95% of human lncRNAs have no functional characterization. Using chromatin conformation and Cap Analysis of Gene Expression (CAGE) data in 18 human cell types, we systematically located genomic regions in spatial proximity to lncRNA genes and identified functional clusters of interacting protein-coding genes, lncRNAs and enhancers. Using these clusters we provide a cell type-specific functional annotation for 7,651 out of 14,198 (53.88%) lncRNAs. LncRNAs tend to have specialized roles in the cell type in which it is first expressed, and to incorporate more general functions as its expression is acquired by multiple cell types during evolution. By analyzing RNA-binding protein and RNA-chromatin interaction data in the context of the spatial genomic interaction map, we explored mechanisms by which these lncRNAs can act.

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