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 re-Searcher: GUI-based bioinformatics tool for simplified genomics data mining of VCF files

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11333
Author(s):  
Daniyar Karabayev ◽  
Askhat Molkenov ◽  
Kaiyrgali Yerulanuly ◽  
Ilyas Kabimoldayev ◽  
Asset Daniyarov ◽  
...  
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
Data Types ◽  
Standard Format ◽  
Standard Data ◽  
Additional Information ◽  
Link Type ◽  
Sequencing Platforms ◽  
User Friendly

Background High-throughput sequencing platforms generate a massive amount of high-dimensional genomic datasets that are available for analysis. Modern and user-friendly bioinformatics tools for analysis and interpretation of genomics data becomes essential during the analysis of sequencing data. Different standard data types and file formats have been developed to store and analyze sequence and genomics data. Variant Call Format (VCF) is the most widespread genomics file type and standard format containing genomic information and variants of sequenced samples. Results Existing tools for processing VCF files don’t usually have an intuitive graphical interface, but instead have just a command-line interface that may be challenging to use for the broader biomedical community interested in genomics data analysis. re-Searcher solves this problem by pre-processing VCF files by chunks to not load RAM of computer. The tool can be used as standalone user-friendly multiplatform GUI application as well as web application (https://nla-lbsb.nu.edu.kz). The software including source code as well as tested VCF files and additional information are publicly available on the GitHub repository (https://github.com/LabBandSB/re-Searcher).

scholarly journals Radiator: a cloud-based framework for deploying re-usable bioinformatics tools

2019 ◽  
Author(s):  
Emily K.W. Lo ◽  
Remy M. Schwab ◽  
Zak Burke ◽  
Patrick Cahan
Keyword(s):  
User Interfaces ◽  
Web Application ◽  
Web Applications ◽  
Cloud Provider ◽  
Web Based ◽  
Lightweight Framework ◽  
Link Type ◽  
Bioinformatics Tools ◽  
Command Line Tool ◽  
Amazon Web Services

AbstractSummaryAccessibility and usability of compute-intensive bioinformatics tools can be increased with simplified web-based graphic user interfaces. However, deploying such tools as web applications presents additional barriers, including the complexity of developing a usable interface, network latency in transferring large datasets, and cost, which we encountered in developing a web-based version of our command-line tool CellNet. Learning and generalizing from this experience, we have devised a lightweight framework, Radiator, to facilitate deploying bioinformatics tools as web applications. To achieve reproducibility, usability, consistent accessibility, throughput, and cost-efficiency, Radiator is designed to be deployed on the cloud. Here, we describe the internals of Radiator and how to use it.Availability and ImplementationCode for Radiator and the CellNet Web Application are freely available at https://github.com/pcahan1 under the MIT license. The CellNet WebApp, Radiator, and Radiator-derived applications can be launched through public Amazon Machine Images from the cloud provider Amazon Web Services (AWS) (https://aws.amazon.com/).

scholarly journals WHONDRS-GUI: a web application for global survey of surface water metabolites

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9277
Author(s):  
Xinming Lin ◽  
Huiying Ren ◽  
Amy E. Goldman ◽  
James C. Stegen ◽  
Timothy D. Scheibe
Keyword(s):  
User Interface ◽  
Surface Water ◽  
Web Application ◽  
Data Types ◽  
Global Survey ◽  
Link Type ◽  
Sampling Campaign ◽  
Domain Integration ◽  
River Corridors ◽  
The Web

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811, which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server (https://xmlin.shinyapps.io/whondrs/).

scholarly journals MiBiOmics: an interactive web application for multi-omics data exploration and integration

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Johanna Zoppi ◽  
Jean-François Guillaume ◽  
Michel Neunlist ◽  
Samuel Chaffron
Keyword(s):  
Web Application ◽  
Biological Systems ◽  
Easy Access ◽  
Omics Data ◽  
Web Based ◽  
Link Type ◽  
Interactive Interface ◽  
Shiny App ◽  
Ordination Techniques ◽  
Scale Characterization

Abstract Background Multi-omics experimental approaches are becoming common practice in biological and medical sciences underlining the need to design new integrative techniques and applications to enable the multi-scale characterization of biological systems. The integrative analysis of heterogeneous datasets generally allows to acquire additional insights and generate novel hypotheses about a given biological system. However, it can become challenging given the often-large size of omics datasets and the diversity of existing techniques. Moreover, visualization tools for interpretation are usually non-accessible to biologists without programming skills. Results Here, we present MiBiOmics, a web-based and standalone application that facilitates multi-omics data visualization, exploration, integration, and analysis by providing easy access to dedicated and interactive protocols. It implements classical ordination techniques and the inference of omics-based (multilayer) networks to mine complex biological systems, and identify robust biomarkers linked to specific contextual parameters or biological states. Conclusions MiBiOmics provides easy-access to exploratory ordination techniques and to a network-based approach for integrative multi-omics analyses through an intuitive and interactive interface. MiBiOmics is currently available as a Shiny app at https://shiny-bird.univ-nantes.fr/app/Mibiomics and as a standalone application at https://gitlab.univ-nantes.fr/combi-ls2n/mibiomics.

scholarly journals GenFam: A web application and database for gene family-based classification and functional enrichment analysis

2018 ◽  
Author(s):  
Renesh Bedre ◽  
Kranthi Mandadi
Keyword(s):  
Gene Family ◽  
Web Application ◽  
High Throughput Sequencing ◽  
Source Code ◽  
Enrichment Analysis ◽  
Gene Families ◽  
Functional Enrichment ◽  
Multiple Testing Correction ◽  
Web Based ◽  
Link Type

ABSTRACTGenome-scale studies using high-throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to guide downstream functional genetic analyses. A popular approach is to determine statistically overrepresented genes in a user-defined list through enrichment analysis tools, which rely on functional annotations of genes based on Gene Ontology (GO) terms. Here, we propose a new approach, GenFam, which allows classification and enrichment of genes based on their gene family, thus simplifying identification of candidate gene families and associated genes that may be relevant to the query. GenFam and its integrated database comprises of three-hundred and eighty-four unique gene families and supports gene family classification and enrichment analyses for sixty plant genomes. Four comparative case studies with plant species belonging to different clades and families were performed using GenFam which demonstrated its robustness and comprehensiveness over preexisting functional enrichment tools. To make it readily accessible for plant biologists, GenFam is available as a web-based application where users can input gene IDs and export enrichment results in both tabular and graphical formats. Users can also customize analysis parameters by choosing from the various statistical enrichment tests and multiple testing correction methods. Additionally, the web-based application, source code and database are freely available to use and download. Website: http://mandadilab.webfactional.com/home/. Source code and database: http://mandadilab.webfactional.com/home/dload/.

scholarly journals MiBiOmics: An interactive web application for multi-omics data exploration and integration

2020 ◽  
Author(s):  
Johanna Zoppi ◽  
Jean-François Guillaume ◽  
Michel Neunlist ◽  
Samuel Chaffron
Keyword(s):  
Web Application ◽  
Biological Systems ◽  
Easy Access ◽  
Omics Data ◽  
Medical Sciences ◽  
Web Based ◽  
Link Type ◽  
Interactive Interface ◽  
Shiny App ◽  
Ordination Techniques

AbstractBackgroundMulti-omics experimental approaches are becoming common practice in biological and medical sciences underlying the need to design new integrative techniques and applications to enable the holistic characterization of biological systems. The integrative analysis of heterogeneous datasets generally allows us to acquire additional insights and generate novel hypotheses about a given biological system. However, it can often become challenging given the large size of omics datasets and the diversity of existing techniques. Moreover, visualization tools for interpretation are usually non-accessible to biologists without programming skills.ResultsHere, we present MiBiOmics, a web-based and standalone application that facilitates multi-omics data visualization, exploration, integration, and analysis by providing easy access to dedicated and interactive protocols. It implements advanced ordination techniques and the inference of omics-based (multi-layer) networks to mine complex biological systems, and identify robust biomarkers linked to specific contextual parameters or biological states.ConclusionsThrough an intuitive and interactive interface, MiBiOmics provides easy-access to ordination techniques and to a network-based approach for integrative multi-omics analyses. MiBiOmics is currently available as a Shiny app at https://shiny-bird.univ-nantes.fr/app/Mibiomics and as a standalone application at https://gitlab.univ-nantes.fr/combi-ls2n/mibiomics.

scholarly journals HiGlass: Web-based Visual Exploration and Analysis of Genome Interaction Maps

2017 ◽  
Author(s):  
Peter Kerpedjiev ◽  
Nezar Abdennur ◽  
Fritz Lekschas ◽  
Chuck McCallum ◽  
Kasper Dinkla ◽  
...  
Keyword(s):  
Open Source ◽  
Visual Exploration ◽  
Visualization Tool ◽  
Data Types ◽  
Experimental Conditions ◽  
Web Based ◽  
Web Technologies ◽  
Link Type

AbstractWe present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online athttp://higlass.ioand is also available as a containerized application that can be run on any platform.

scholarly journals CircularLogo: A lightweight web application to visualize intra-motif dependencies

2017 ◽  
Author(s):  
Zhenqing Ye ◽  
Tao Ma ◽  
Michael T. Kalmbach ◽  
Surendra Dasari ◽  
Jean-Pierre A. Kocher ◽  
...  
Keyword(s):  
Binding Sites ◽  
Web Application ◽  
Source Code ◽  
Sequence Logo ◽  
Rna Motifs ◽  
Biomolecular Structure ◽  
Web Based ◽  
Link Type ◽  
Web Framework ◽  
Interactive Application

AbstractBackgroundThe sequence logo has been widely used to represent DNA or RNA motifs for more than three decades. Despite its intelligibility and intuitiveness, the traditional sequence logo is unable to display the intra-motif dependencies and therefore is insufficient to fully characterize nucleotide motifs. Many methods have been developed to quantify the intra-motif dependencies, but fewer tools are available for visualization.ResultWe developed CircularLogo, a web-based interactive application, which is able to not only visualize the position-specific nucleotide consensus and diversity but also display the intra-motif dependencies. Applying CircularLogo to HNF6 binding sites and tRNA sequences demonstrated its ability to show intra-motif dependencies and intuitively reveal biomolecular structure. CircularLogo is implemented in JavaScript and Python based on the Django web framework. The program’s source code and user’s manual are freely available at http://circularlogo.sourceforge.net. CircularLogo web server can be accessed from http://bioinformaticstools.mayo.edu/circularlogo/index.html.ConclusionCircularLogo is an innovative web application that is specifically designed to visualize and interactively explore intra-motif dependencies.

scholarly journals NetWheels: A web application to create high quality peptide helical wheel and net projections

2018 ◽  
Author(s):  
A.R. Mól ◽  
M.S. Castro ◽  
W. Fontes
Keyword(s):  
Web Application ◽  
Secondary Structures ◽  
Two Dimensions ◽  
Helical Structures ◽  
High Quality ◽  
Web Based ◽  
Link Type ◽  
Helical Wheel ◽  
Intramolecular Bonding

AbstractHelices are one of the most common secondary structures found in peptides and proteins. The wheel and net projections have been proposed to represent in two dimensions the tridimensional helical structures and facilitate the observation of their properties, especially in terms of residues polarity and intramolecular bonding. Nevertheless, there are few software options to create these projections. We have developed a web-based application that has several futures to create, customize and export these projections and is freely available at http://lbqp.unb.br/NetWheels.

scholarly journals Annot: a Django-based sample, reagent, and experiment metadata tracking system

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Elmar Bucher ◽  
Cheryl J. Claunch ◽  
Derrick Hee ◽  
Rebecca L. Smith ◽  
Kaylyn Devlin ◽  
...  
Keyword(s):  
Data Analysis ◽  
Web Application ◽  
Large Scale ◽  
Tracking System ◽  
Controlled Vocabulary ◽  
File Format ◽  
Robust Solution ◽  
Microarray Study ◽  
Link Type ◽  
Experimental Protocols

Abstract Background In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task. Results Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot’s implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R (https://www.r-project.org/) or Pandas, Python’s data analysis library (https://pandas.pydata.org/). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers. Conclusions Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

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