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 Knowledge.Bio: A Web Application for Exploring, Building and Sharing Webs of Biomedical Relationships Mined from PubMed

2016 ◽  
Author(s):  
Richard Bruskiewich ◽  
Kenneth Huellas-Bruskiewicz ◽  
Farzin Ahmed ◽  
Rajaram Kaliyaperumal ◽  
Mark Thompson ◽  
...  
Keyword(s):  
User Interface ◽  
Text Mining ◽  
Graphical User Interface ◽  
Biomedical Research ◽  
Web Application ◽  
Source Code ◽  
Research Literature ◽  
Knowledge Networks ◽  
Link Type ◽  
Web Platform

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]

scholarly journals NanoPack: visualizing and processing long read sequencing data

2017 ◽  
Author(s):  
Wouter De Coster ◽  
Svenn D’Hert ◽  
Darrin T. Schultz ◽  
Marc Cruts ◽  
Christine Van Broeckhoven
Keyword(s):  
Web Service ◽  
Graphical User Interface ◽  
Source Code ◽  
Supplementary Information ◽  
Command Line ◽  
Sequencing Data ◽  
Link Type ◽  
Oxford Nanopore ◽  
Long Read ◽  
Oxford Nanopore Technologies

AbstractSummary: Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and Implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 Licence. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Contact:[email protected] information: Supplementary tables and figures are available at Bioinformatics online.

scholarly journals Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files

2015 ◽  
Vol 14 ◽  
pp. CIN.S26470 ◽  
Author(s):  
Richard P. Finney ◽  
Qing-Rong Chen ◽  
Cu V. Nguyen ◽  
Chih Hao Hsu ◽  
Chunhua Yan ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Reference Genome ◽  
Source Code ◽  
Software Tool ◽  
Command Line ◽  
Sequencing Data ◽  
Genome Data ◽  
Command Line Tool ◽  
Portable Software ◽  
Microsoft Windows

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview . The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview .

scholarly journals idCOV: a pipeline for quick clade identification of SARS-CoV-2 isolates

2020 ◽  
Author(s):  
Xun Zhu ◽  
Ti-Cheng Chang ◽  
Richard Webby ◽  
Gang Wu
Keyword(s):  
Personal Computer ◽  
Source Code ◽  
Command Line ◽  
Sequencing Data ◽  
Link Type ◽  
Public Dataset ◽  
Virus Isolates

AbstractidCOV is a phylogenetic pipeline for quickly identifying the clades of SARS-CoV-2 virus isolates from raw sequencing data based on a selected clade-defining marker list. Using a public dataset, we show that idCOV can make equivalent calls as annotated by Nextstrain.org on all three common clade systems using user uploaded FastQ files directly. Web and equivalent command-line interfaces are available. It can be deployed on any Linux environment, including personal computer, HPC and the cloud. The source code is available at https://github.com/xz-stjude/idcov. A documentation for installation can be found at https://github.com/xz-stjude/idcov/blob/master/README.md.

scholarly journals BatchServer: a web server for batch effect evaluation, visualization and correction

2020 ◽  
Author(s):  
Tiansheng Zhu ◽  
Guo-Bo Chen ◽  
Chunhui Yuan ◽  
Rui Sun ◽  
Fangfei Zhang ◽  
...  
Keyword(s):  
Web Server ◽  
Batch Effect ◽  
Variance Component Analysis ◽  
Data Sets ◽  
Batch Effects ◽  
Source Codes ◽  
Link Type ◽  
R Shiny ◽  
User Friendly ◽  
Web Platform

AbstractBatch effects are unwanted data variations that may obscure biological signals, leading to bias or errors in subsequent data analyses. Effective evaluation and elimination of batch effects are necessary for omics data analysis. In order to facilitate the evaluation and correction of batch effects, here we present BatchSever, an open-source R/Shiny based user-friendly interactive graphical web platform for batch effects analysis. In BatchServer we introduced autoComBat, a modified version of ComBat, which is the most widely adopted tool for batch effect correction. BatchServer uses PVCA (Principal Variance Component Analysis) and UMAP (Manifold Approximation and Projection) for evaluation and visualizion of batch effects. We demonstate its application in multiple proteomics and transcriptomic data sets. BatchServer is provided at https://lifeinfo.shinyapps.io/batchserver/ as a web server. The source codes are freely available at https://github.com/guomics-lab/batch_server.

scholarly journals ASaiM: a Galaxy-based framework to analyze raw shotgun data from microbiota

2017 ◽  
Author(s):  
Bérénice Batut ◽  
Kévin Gravouil ◽  
Clémence Defois ◽  
Saskia Hiltemann ◽  
Jean-François Brugère ◽  
...  
Keyword(s):  
Technological Progress ◽  
Source Code ◽  
Command Line ◽  
Bioinformatic Tools ◽  
Link Type ◽  
Data Analyses ◽  
The Galaxy ◽  
Sequencing Platforms ◽  
User Friendly ◽  
New Generation

AbstractBackgroundNew generation of sequencing platforms coupled to numerous bioinformatics tools has led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies.FindingsWe therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides a curated collection of tools to explore and visualize taxonomic and functional information from raw amplicon, metagenomic or metatranscriptomic sequences. To guide different analyses, several customizable workflows are included. All workflows are supported by tutorials and Galaxy interactive tours to guide the users through the analyses step by step. ASaiM is implemented as Galaxy Docker flavour. It is scalable to many thousand datasets, but also can be used a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io/)ConclusionsBased on the Galaxy framework, ASaiM offers sophisticated analyses to scientists without command-line knowledge. ASaiM provides a powerful framework to easily and quickly explore microbiota data in a reproducible and transparent environment.

scholarly journals Phigaro: high throughput prophage sequence annotation

2019 ◽  
Author(s):  
Elizaveta V. Starikova ◽  
Polina O. Tikhonova ◽  
Nikita A. Prianichnikov ◽  
Chris M. Rands ◽  
Evgeny M. Zdobnov ◽  
...  
Keyword(s):  
Test Data ◽  
High Throughput ◽  
Source Code ◽  
Sequence Annotation ◽  
Command Line ◽  
Link Type ◽  
Genome Maps ◽  
Transposon Insertion ◽  
Prophage Sequence

AbstractSummaryPhigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It provides putative taxonomic annotations that can distinguish tailed from non-tailed phages. It is applicable for mining prophage regions from large metagenomic datasets.AvailabilitySource code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.

scholarly journals metaCOVID: An R-Shiny application for living meta-analyses of COVID-19 trials

2021 ◽  
Author(s):  
Theodoros Evrenoglou ◽  
Isabelle Boutron ◽  
Anna Chaimani
Keyword(s):  
Evidence Synthesis ◽  
Source Code ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Preventive Interventions ◽  
Primary Interest ◽  
Link Type ◽  
R Shiny ◽  
Meta Analyses ◽  
Shiny Application

Abstract“Living” evidence synthesis is of primary interest for decision-makers to overcome the COVID-19 pandemic. The COVID-NMA provides open-access living meta-analyses assessing different therapeutic and preventive interventions. Data are posted on a platform (https://covid-nma.com/) and analyses are updated every week. However, guideline developers and other stakeholders also need to investigate the data and perform their own analyses. This requires resources, time, statistical expertise, and software knowledge. To assist them, we created the “metaCOVID” application which, based on automation processes, facilitates the fast exploration of the data and the conduct of analyses tailored to end-users needs. metaCOVID has been created in R and is freely available as an R-Shiny application. The application conducts living meta-analyses for every outcome. Several options are available for subgroup and sensitivity analyses. The results are presented in downloadable forest plots. metaCOVID is freely available from https://covid-nma.com/metacovid/ and the source code from https://github.com/TEvrenoglou/metaCovid.

scholarly journals Visualizing Neural Machine Translation Attention and Confidence

2017 ◽  
Vol 109 (1) ◽  
pp. 39-50 ◽  
Author(s):  
Matīss Rikters ◽  
Mark Fishel ◽  
Ondřej Bojar
Keyword(s):  
Machine Translation ◽  
Command Line ◽  
Web Based ◽  
Neural Machine Translation ◽  
Link Type ◽  
Translation Systems

Abstract In this article, we describe a tool for visualizing the output and attention weights of neural machine translation systems and for estimating confidence about the output based on the attention. Our aim is to help researchers and developers better understand the behaviour of their NMT systems without the need for any reference translations. Our tool includes command line and web-based interfaces that allow to systematically evaluate translation outputs from various engines and experiments. We also present a web demo of our tool with examples of good and bad translations: http://ej.uz/nmt-attention.

scholarly journals MT-ComparEval: Graphical evaluation interface for Machine Translation development

2015 ◽  
Vol 104 (1) ◽  
pp. 63-74 ◽  
Author(s):  
Ondřej Klejch ◽  
Eleftherios Avramidis ◽  
Aljoscha Burchardt ◽  
Martin Popel
Keyword(s):  
Comparative Analysis ◽  
User Interface ◽  
Machine Translation ◽  
Graphical User Interface ◽  
Statistical Significance ◽  
Web Based ◽  
Link Type ◽  
Evaluation Panel ◽  
N Gram

Abstract The tool described in this article has been designed to help MT developers by implementing a web-based graphical user interface that allows to systematically compare and evaluate various MT engines/experiments using comparative analysis via automatic measures and statistics. The evaluation panel provides graphs, tests for statistical significance and n-gram statistics. We also present a demo server http://wmt.ufal.cz with WMT14 and WMT15 translations.

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