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 ◽  
...  

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.

2018 ◽  
Author(s):  
Renesh Bedre ◽  
Kranthi Mandadi

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/.


2019 ◽  
Author(s):  
Wenlong Jia ◽  
Hechen Li ◽  
Shiying Li ◽  
Shuaicheng Li

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]


2019 ◽  
Vol 35 (21) ◽  
pp. 4462-4464
Author(s):  
Jordan H Creed ◽  
Garrick Aden-Buie ◽  
Alvaro N Monteiro ◽  
Travis A Gerke

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.


2016 ◽  
Author(s):  
Richard Bruskiewich ◽  
Kenneth Huellas-Bruskiewicz ◽  
Farzin Ahmed ◽  
Rajaram Kaliyaperumal ◽  
Mark Thompson ◽  
...  

AbstractKnowledge.Bio is a web platform that enhances access and interpretation of knowledge networks extracted from biomedical research literature. The interaction is mediated through a collaborative graphical user interface for building and evaluating maps of concepts and their relationships, alongside associated evidence. In the first release of this platform, conceptual relations are drawn from the Semantic Medline Database and the Implicitome, two compleme ntary resources derived from text mining of PubMed abstracts.Availability— Knowledge.Bio is hosted at http://knowledge.bio/ and the open source code is available at http://bitbucket.org/sulab/kb1/.Contact— [email protected]; [email protected]


2019 ◽  
Author(s):  
Amit Min ◽  
Erika Deoudes ◽  
Marielle L. Bond ◽  
Eric S. Davis ◽  
Douglas H. Phanstiel

Protein phosphatases and kinases play critical roles in a host of biological processes and diseases via the removal and addition of phosphoryl groups. While kinases have been extensively studied for decades, recent findings regarding the specificity and activities of phosphatases have generated an increased interest in targeting phosphatases for pharmaceutical development. This increased focus has created a need for methods to visualize this important class of proteins within the context of the entire phosphatase protein family. Here, we present CoralP, an interactive web application for the generation of customizable, publication-quality representations of human phosphatome data. Phosphatase attributes can be encoded through edge colors, node colors, and node sizes. CoralP is the first and currently the only tool designed for phosphatome visualization and should be of great use to the signaling community. The source code and web application are available at https://github.com/PhanstielLab/coralp and http://phanstiel-lab.med.unc.edu/coralp respectively.


2018 ◽  
Author(s):  
Marc Chakiachvili ◽  
Sylvain Milanesi ◽  
Anne-Muriel Arigon Chifolleau ◽  
Vincent Lefort

AbstractSummary: WAVES is a web application dedicated to bioinformatic tool integration. It provides an efficient way to implement a service for any bioinformatic software. Such services are automatically made available in three ways: web pages, web forms to include in remote websites, and a RESTful web services API to access remotely from applications. In order to fulfill the service’s computational needs, WAVES can perform computation on various resources and environments, such as Galaxy instances.Availability and implementation: WAVES was developed with Django, a Python-based web framework. It was designed as a reusable web application. It is fully portable, as only a Python installation is required to run Django. It is licensed under GNU General Public License. Source code, documentation with examples and demo are available from http://www.atgc-montpellier.fr/waves/.Contact:[email protected]


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Rodolfo S. Allendes Osorio ◽  
Lokesh P. Tripathi ◽  
Kenji Mizuguchi

Abstract Background When visually comparing the results of hierarchical clustering, the differences in the arrangements of components are of special interest. However, in a biological setting, identifying such differences becomes less straightforward, as the changes in the dendrogram structure caused by permuting biological replicates, do not necessarily imply a different biological interpretation. Here, we introduce a visualization tool to help identify biologically similar topologies across different clustering results, even in the presence of replicates. Results Here we introduce CLINE, an open-access web application that allows users to visualize and compare multiple dendrogram structures, by visually displaying the links between areas of similarity across multiple structures. Through the use of a single page and a simple user interface, the user is able to load and remove structures form the visualization, change some aspects of their display and set the parameters used to match cluster topology across consecutive pairs of dendrograms. Conclusions We have implemented a web-tool that allows the users to visualize different dendrogram structures, showing not only the structures themselves, but also linking areas of similarity across multiple structures. The software is freely available at http://mizuguchilab.org/tools/cline/. Also, the source code, documentation and installation instructions are available on GitHub at https://github.com/RodolfoAllendes/cline/.


PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243609
Author(s):  
Yi-An Chen ◽  
Jonguk Park ◽  
Yayoi Natsume-Kitatani ◽  
Hitoshi Kawashima ◽  
Attayeb Mohsen ◽  
...  

With an ever-increasing interest in understanding the relationships between the microbiota and the host, more tools to map, analyze and interpret these relationships have been developed. Most of these tools, however, focus on taxonomic profiling and comparative analysis among groups, with very few analytical tools designed to correlate microbiota and the host phenotypic data. We have developed a software program for creating a web-based integrative database and analysis platform called MANTA (Microbiota And pheNoType correlation Analysis platform). In addition to storing the data, MANTA is equipped with an intuitive user interface that can be used to correlate the microbial composition with phenotypic parameters. Using a case study, we demonstrated that MANTA was able to quickly identify the significant correlations between microbial abundances and phenotypes that are supported by previous studies. Moreover, MANTA enabled the users to quick access locally stored data that can help interpret microbiota-phenotype relations. MANTA is available at https://mizuguchilab.org/manta/ for download and the source code can be found at https://github.com/chenyian-nibio/manta.


2019 ◽  
Author(s):  
Emily K.W. Lo ◽  
Remy M. Schwab ◽  
Zak Burke ◽  
Patrick Cahan

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/).


2016 ◽  
Author(s):  
Julien Delafontaine ◽  
Alexandre Masselot ◽  
Robin Liechti ◽  
Dmitry Kuznetsov ◽  
Ioannis Xenarios ◽  
...  

AbstractSummary: Varapp is an open-source web application to filter variants from large sets of exome data stored in a relational database. Varapp offers a reactive graphical user interface, very fast data pro-cessing, security and facility to save, reproduce and shareresults. Typically, a few seconds suffice to apply non-trivial filters to a set of half a million variants and extract a handful of potential clinically relevant targets. Varapp implements different scenarios for Mendelian diseases (dominant, recessive, de novo, X-linked, andcompound heterozygous), and allows searching for variants in genes or chro-mosomal regions of interest.Availability: The application is made of a Javascript front-end and a Python back-end. Its source code is hosted at https://github.com/varapp. A demo version isavailable at https://varapp-demo.vital-it.ch. The full documentation can be found at https://varapp-demo.vital-it.ch/docs.Contact:[email protected]


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