scholarly journals VolcanoR - web service to produce volcano plots and do basic enrichment analysis

2017 ◽  
Author(s):  
Vladimir Naumov ◽  
Ivan Balashov ◽  
Vadim Lagutin ◽  
Pavel Borovikov ◽  
Alexey Alexeev
Keyword(s):  
Web Service ◽  
Input Data ◽  
Enrichment Analysis ◽  
P Value ◽  
Web Based ◽  
Link Type ◽  
Volcano Plots ◽  
R Shiny ◽  
Differential Gene ◽  
Publication Quality

AbstractSummary: We introduce VolcanoR - web based tool to analyse results of differential gene expression. It takes a table containing gene name p-value and foldChange as input data. It can produce publication quality volcano plots, apply different p-value and fold change thresholds and do basic GeneOntology and KEGG enrichment analysis with selected gene set. For now it supports H.sapiens, R.norvegicus and M.musclus.Availability and Implementation: VolcanoR is wtitten using R Shiny framework. It is publically available at http://volcanor.bioinf.su or stand-alone application, that can be downloaded at https://github.com/vovalive/volcanoRContact: [email protected]

scholarly journals HD-eXplosion: visualization of hydrogen–deuterium exchange data as chiclet and volcano plots with statistical filtering

2020 ◽  
Author(s):  
Naifu Zhang ◽  
Xiaohe Yu ◽  
Xinchao Zhang ◽  
Sheena D’Arcy
Keyword(s):  
Source Code ◽  
Deuterium Exchange ◽  
Hydrogen Deuterium Exchange ◽  
Web Based ◽  
Data Presentation ◽  
Software Packages ◽  
Volcano Plots ◽  
Hydrogen Deuterium ◽  
Exchange Data ◽  
Publication Quality

Abstract Summary Hydrogen–Deuterium eXchange coupled to mass spectrometry is a powerful tool for the analysis of protein dynamics and interactions. Bottom-up experiments looking at deuterium uptake differences between various conditions are the most common. These produce multi-dimensional data that can be challenging to depict in a single visual format. Each user must also set significance thresholds to define meaningful differences and make these apparent in data presentation. To assist in this process, we have created HD-eXplosion, an open-source, web-based application for the generation of chiclet and volcano plots with statistical filters. HD-eXplosion fills a void in available software packages and produces customizable plots that are publication quality. Availability and implementation The HD-eXplosion application is available at http://hd-explosion.utdallas.edu. The source code can be found at https://github.com/HD-Explosion.

scholarly journals Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists

2017 ◽  
Author(s):  
Xun Zhu ◽  
Thomas Wolfgruber ◽  
Austin Tasato ◽  
David G. Garmire ◽  
Lana X Garmire
Keyword(s):  
Single Cell ◽  
Enrichment Analysis ◽  
Graphical Interface ◽  
Analysis Pipeline ◽  
Web Based ◽  
Cell Clustering ◽  
Gene Filtering ◽  
Study Heterogeneity ◽  
Differential Gene ◽  
Cell Series

AbstractBackgroundSingle-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level.Computational methods to process scRNA-Seq have limited accessibility to bench scientists as they require significant amounts of bioinformatics skills.ResultsWe have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene filtering, geneexpression normalization, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein-networ interaction visualization, and pseudo-time cell series construction.ConclusionsGranatum enables broad adoption of scRNA-Seq technology by empowering the bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use athttp://garmiregroup.org/granatum/app

scholarly journals DynaVenn: web-based computation of the most significant overlap between ordered sets

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Jérémy Amand ◽  
Tobias Fehlmann ◽  
Christina Backes ◽  
Andreas Keller
Keyword(s):  
Web Service ◽  
Primary Study ◽  
Finite Collection ◽  
P Value ◽  
Ordered Sets ◽  
Web Based ◽  
Venn Diagrams ◽  
Disease Biomarker ◽  
Euler Diagrams ◽  
Improved Performance

Abstract Background In many research disciplines, ordered lists are compared. One example is to compare a subset of all significant genes or proteins in a primary study to those in a replication study. Often, the top of the lists are compared using Venn diagrams, ore more precisely Euler diagrams (set diagrams showing logical relations between a finite collection of different sets). If different cohort sizes, different techniques or algorithms for evaluation were applied, a direct comparison of significant genes with a fixed threshold can however be misleading and approaches comparing lists would be more appropriate. Results We developed DynaVenn, a web-based tool that incrementally creates all possible subsets from two or three ordered lists and computes for each combination a p-value for the overlap. Respectively, dynamic Venn diagrams are generated as graphical representations. Additionally an animation is generated showing how the most significant overlap is reached by backtracking. We demonstrate the improved performance of DynaVenn over an arbitrary cut-off approach on an Alzheimer’s Disease biomarker set. Conclusion DynaVenn combines the calculation of the most significant overlap of different cohorts with an intuitive visualization of the results. It is freely available as a web service at http://www.ccb.uni-saarland.de/dynavenn.

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 UROPA GUI: A web platform for genomic region annotation

2018 ◽  
Author(s):  
Hendrik Schultheis ◽  
Jens Preussner ◽  
Annika Fust ◽  
Mette Bentsen ◽  
Carsten Kuenne ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Bioinformatics Analysis ◽  
Source Code ◽  
Genomic Region ◽  
Command Line ◽  
Web Based ◽  
Link Type ◽  
R Shiny ◽  
Considerable Impact ◽  
Web Platform

AbstractThe annotation of genomic ranges such as peaks resulting from ChIP-seq/ATAC-seq or other techniques represents a fundamental task of bioinformatics analysis with considerable impact on many downstream analyses. In our previous work, we introduced the Universal Robust Peak Annotator (UROPA), a flexible command line based tool which improves upon the functionality of existing annotation software. In order to reduce the complexity for biologists and clinicians, we have implemented an intuitive web-based graphical user interface (GUI) and fully functional service platform for UROPA. This extension will empower all users to generate annotations for regions of interest interactively.Availability and ImplementationThe open source UROPA GUI server was implemented in R Shiny and Python and is available from http://loosolab.mpi-bn.mpg.de. The source code of our App can be downloaded at https://github.molgen.mpg.de/loosolab/UROPA_GUI under the MIT license.

scholarly journals BPG: Seamless, Automated and Interactive Visualization of Scientific Data

2017 ◽  
Author(s):  
Christine P’ng ◽  
Jeffrey Green ◽  
Lauren C. Chong ◽  
Daryl Waggott ◽  
Stephenie D. Prokopec ◽  
...  
Keyword(s):  
Open Source ◽  
Interactive Visualization ◽  
Scientific Data ◽  
High Dimensional ◽  
Seamless Integration ◽  
Web Based ◽  
Link Type ◽  
Interactive Tool ◽  
High Dimensional Datasets ◽  
Publication Quality

AbstractWe introduce BPG, an easy-to-use framework for generating publication-quality, highly-customizable plots in the R statistical environment. This open-source package includes novel methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it ideal for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for seamless integration with computational pipelines. BPG is available at http://labs.oicr.on.ca/boutros-lab/software/bpg

scholarly journals Rancang Bangun Aplikasi Mobile Survey Pendamping Program Keluarga Harapan (Studi Kasus: UPPKH Dinas Sosial dan Tenaga Kerja Kota Batu)

2018 ◽  
Vol 1 (2) ◽  
pp. 90
Author(s):  
Muhammad Rojib Saiful ◽  
Galih Wasis Wicaksono ◽  
Nur Hayatin
Keyword(s):  
Web Service ◽  
Input Data ◽  
Web Based ◽  
Mobile Survey

<em>UPPKH Dinas Sosial dan Tenaga Kerja Kota Batu ini, merupakan satu dari beberapa instansi pemerintah yang belum menerapkan sistem informasi manajemen pengolahan data dan masih melakukan input data di setiap aktivitasnya masih secara manual. Hal itu menjadikan kendala bagi instansi pemerintahan tersebut untuk meningkatkan kinerja para pendamping dalam menyediakan informasi yang efektif dan efisien. Pengolahan data yang masih manual ini menimbulkan berbagai masalah. Diantaranya yang timbul dari permasalahan pendamping dalam menjalankan tiap tugasnya harus menunggu data dari admin untuk survei ke setiap calon anggota peserta PKH. Dan permasalahan yang lain yaitu sulitnya admin untuk mengetahui informasi laporan data PKH.</em><em>  Dan untuk mengatasi permasalahan yang ada pada kasus ini penulis menganalisis dan merancang sebuah aplikasi yang diharapkan dapat membantu tugas para pendamping dan admin, dimulai dari pengumpulan data menggunakan wawancara, observasi, dan penelitian kepustakaan. Dan aplikasi yang digunakan dalam implementasi sistem, yaitu database MySQL, Webservice, PHP Codeigniter dan Android sebagai bahasa pemrogramannya. Sistem ini mengintegrasikan aplikasi android dengan aplikasi web based menggunakan web service. Web Service menyediakan standar komunikasi di antara berbagai aplikasi software yang berbeda dan dapat berjalan di berbagai platform maupun framework. Sistem ini dibuat untuk membantu mempercepat proses penyelesaian pekerjaan seperti pada proses pendamping dan admin.</em>

scholarly journals figureComposer: A web-based interactive multi-panel bio-infographic designing tool

2020 ◽  
Author(s):  
Kejie Li ◽  
Jessica Hurt ◽  
Christopher D. Whelan ◽  
Ravi Challa ◽  
Dongdong Lin ◽  
...  
Keyword(s):  
High Resolution ◽  
Web Tool ◽  
Bioinformatics Tool ◽  
Web Based ◽  
Link Type ◽  
High Resolution Images ◽  
Fit For Purpose ◽  
Programming Skills ◽  
User Friendly ◽  
Publication Quality

AbstractBackgroundMany fit-for-purpose bioinformatics tools generate plots to investigate data quality and illustrate findings. However, assembling individual plots in different formats from various sources into one high-resolution figure requires mastery of commercial tools or even programming skills. In addition, it is a time-consuming and sometimes frustrating process even for scientists with modest computational skills.ResultsWe developed figureComposer, a web-based bioinformatics tool that interactively arranges high-resolution images in various formats, mainly SVG to produce one multi-panel publication-quality composite figure in both PDF and interactive HTML formats in a user-friendly matter, requiring no programming skills.ConclusionsfigureComposer is open-source and publicly available web tool that can be accessed online at https://baohongz.github.io/figureComposer while the source code is provided at https://github.com/baohongz/figureComposer.

scholarly journals OUTBREAK: a user-friendly georeferencing online tool for disease surveillance

2021 ◽  
Vol 54 (1) ◽  
Author(s):  
Raúl Arias-Carrasco ◽  
Jeevan Giddaluru ◽  
Lucas E. Cardozo ◽  
Felipe Martins ◽  
Vinicius Maracaja-Coutinho ◽  
...  
Keyword(s):  
Real Time ◽  
Disease Surveillance ◽  
Input Data ◽  
Policy Decisions ◽  
Web Tool ◽  
Web Based ◽  
Online Tool ◽  
Link Type ◽  
Health Authorities ◽  
User Friendly

AbstractThe current COVID-19 pandemic has already claimed more than 3.7 million victims and it will cause more deaths in the coming months. Tools that track the number and locations of cases are critical for surveillance and help in making policy decisions for controlling the outbreak. However, the current surveillance web-based dashboards run on proprietary platforms, which are often expensive and require specific computational knowledge. We developed a user-friendly web tool, named OUTBREAK, that facilitates epidemic surveillance by showing in an animated graph the timeline and geolocations of cases of an outbreak. It permits even non-specialist users to input data most conveniently and track outbreaks in real-time. We applied our tool to visualize the SARS 2003, MERS, and COVID19 epidemics, and provided them as examples on the website. Through the zoom feature, it is also possible to visualize cases at city and even neighborhood levels. We made the tool freely available at https://outbreak.sysbio.tools/. OUTBREAK has the potential to guide and help health authorities to intervene and minimize the effects of outbreaks.

scholarly journals Omics BioAnalytics: Reproducible Research using R Shiny and Alexa

2020 ◽  
Author(s):  
Amrit Singh ◽  
Scott J. Tebbutt ◽  
Bruce M. McManus
Keyword(s):  
Molecular Mechanisms ◽  
Reproducible Research ◽  
Web Based ◽  
Domain Experts ◽  
Link Type ◽  
Web Framework ◽  
Biological Domain ◽  
R Shiny ◽  
Interactive Visualizations ◽  
Health And Disease

AbstractSummaryHigh-throughput technologies produce complex high-dimensional datasets which are analyzed using a variety of ever-evolving bioinformatics tools. Well-designed web frameworks enable more intuitive and efficient analysis such that less time is spent on coding and more time is spent on interpretation of results and addressing insightful biological questions aided by interactive visualizations. Here, we present Omics BioAnalytics, a full-service Web framework that enables comprehensive, multi-level characterization, analysis, and integration of omics datasets. Blending web-based (R Shiny) and voice-based (Amazon’s Alexa) analytics, Omics BioAnalytics can be used both by expert computational biologists and non-coding biological domain experts, alike. Our web framework can be utilized to explore complex datasets and identify biosignatures and discriminative biomarkers of health and disease processes, and generate testable hypotheses relating to underlying molecular mechanisms.AvailabilityOmics BioAnalytics is freely available at https://github.com/singha53/omicsBioAnalytics and the web app is deployed at https://amritsingh.shinyapps.io/omicsBioAnalytics/. The source code for the companion Alexa Skill can be found at https://github.com/singha53/omics-bioanalytics-alexa-skill.

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