scholarly journals TaxonTableTools - A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data

2020 ◽  
Author(s):  
Till-Hendrik Macher ◽  
Arne J. Beermann ◽  
Florian Leese
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Biological Information ◽  
Analysis Software ◽  
Rarefaction Analysis ◽  
Link Type ◽  
Dna Metabarcoding ◽  
Traditional Taxonomy ◽  
Reproducible Analysis ◽  
Downstream Analysis

AbstractDNA metabarcoding is increasingly used in research and application to assess biodiversity. Powerful analysis software exists to process raw data. However, when it comes to the translation of sequence read data into biological information many end users with limited bioinformatic expertise struggle with the downstream analysis and explore data only to a minor extent. Thus, there is a growing need for easy-to-use, graphical user interface (GUI) analysis software to analyse and visualise DNA metabarcoding data. We here present TaxonTableTools (TTT), a new platform independent GUI software that aims to fill this gap by providing simple and reproducible analysis and visualisation workflows. TTT uses a so-called “TaXon table” as input. This format can easily be generated within TTT from two input files: a read table and a taxonomy table that can be obtained by various published metabarcoding pipelines. TTT analysis and visualisation modules include e.g. Venn diagrams to compare taxon overlap among replicates, samples or among different analysis methods. It analyses and visualises basic statistics such as read proportion per taxon as well as more sophisticated visualisation such as interactive Krona charts for taxonomic data exploration. Various ecological analyses such as alpha or beta diversity estimates, and rarefaction analysis ordination plots can be produced directly. Data can be explored also in formats required by traditional taxonomy-based analyses of regulatory bioassessment programs. TTT comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) and the Python package index (https://pypi.org/project/taxontabletools/).

scholarly journals MuSA: a graphical user interface for multi-OMICs data integration in radiogenomic studies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mario Zanfardino ◽  
Rossana Castaldo ◽  
Katia Pane ◽  
Ornella Affinito ◽  
Marco Aiello ◽  
...  
Keyword(s):  
User Interface ◽  
Data Integration ◽  
Graphical User Interface ◽  
Data Science ◽  
Heterogeneous Data ◽  
Biological Information ◽  
Omics Data ◽  
Correlation Clustering ◽  
Downstream Analysis ◽  
Omics Data Integration

AbstractAnalysis of large-scale omics data along with biomedical images has gaining a huge interest in predicting phenotypic conditions towards personalized medicine. Multiple layers of investigations such as genomics, transcriptomics and proteomics, have led to high dimensionality and heterogeneity of data. Multi-omics data integration can provide meaningful contribution to early diagnosis and an accurate estimate of prognosis and treatment in cancer. Some multi-layer data structures have been developed to integrate multi-omics biological information, but none of these has been developed and evaluated to include radiomic data. We proposed to use MultiAssayExperiment (MAE) as an integrated data structure to combine multi-omics data facilitating the exploration of heterogeneous data. We improved the usability of the MAE, developing a Multi-omics Statistical Approaches (MuSA) tool that uses a Shiny graphical user interface, able to simplify the management and the analysis of radiogenomic datasets. The capabilities of MuSA were shown using public breast cancer datasets from TCGA-TCIA databases. MuSA architecture is modular and can be divided in Pre-processing and Downstream analysis. The pre-processing section allows data filtering and normalization. The downstream analysis section contains modules for data science such as correlation, clustering (i.e., heatmap) and feature selection methods. The results are dynamically shown in MuSA. MuSA tool provides an easy-to-use way to create, manage and analyze radiogenomic data. The application is specifically designed to guide no-programmer researchers through different computational steps. Integration analysis is implemented in a modular structure, making MuSA an easily expansible open-source software.

scholarly journals TaxonTableTools - A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data

2021 ◽  
Vol 4 ◽  
Author(s):  
Till-Hendrik Macher ◽  
Arne Beermann ◽  
Florian Leese
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Distribution Patterns ◽  
Assessment Tools ◽  
Biological Information ◽  
Distribution Data ◽  
Global Biodiversity Information Facility ◽  
Data Set ◽  
Wide Range ◽  
Dna Metabarcoding

DNA-based identification methods, such as DNA metabarcoding, are increasingly used as biodiversity assessment tools in research and environmental management. Although powerful analysis software exists to process raw data, the translation of sequence read data into biological information and downstream analyses may be difficult for end users with limited expertise in bioinformatics. Thus, the need for easy-to-use, graphical user interface (GUI) software to analyze and visualize DNA metabarcoding data is growing. Here we present TaxonTableTools (TTT), a new platform-independent GUI that aims to fill this gap by providing simple, reproducible analysis and visualization workflows. The input format of TTT is a so-called "TaXon table". This data format can easily be generated within TTT from two common file formats that can be obtained using various published DNA metabarcoding pipelines: a read table and a taxonomy table. TTT offers a wide range of processing, filtering and analysis modules. The user can analyze and visualize basic statistics, such as read proportion per taxon, as well as more sophisticated visualizations such as interactive Krona charts for taxonomic data exploration, or complex parallel category diagrams to assess species distribution patterns. Venn diagrams can be calculated to compare taxon overlap among replicates, samples, or analysis methods. Various ecological analyses can be produced directly, including alpha or beta diversity estimates, rarefaction analyses, and principal coordinate or non-metric multidimensional scaling plots. The taxonomy of a data set can be validated via the Global Biodiversity Information Facility (GBIF) API to check for synonyms and spelling mistakes. Furthermore, geographical distribution data can be automatically downloaded from GBIF. Additionally, TTT offers a conversion tool for DNA metabarcoding data into formats required for traditional, taxonomy-based analyses performed by regulatory bioassessment programs. Beyond that, TTT is able to produce fully interactive html-based graphics that can be analyzed in any web browser. The software comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) or the Python package index (https://pypi.org/project/taxontabletools/).

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.

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 LexOPS: An R package and user interface for the controlled generation of word stimuli

2020 ◽  
Vol 52 (6) ◽  
pp. 2372-2382
Author(s):  
Jack E. Taylor ◽  
Alistair Beith ◽  
Sara C. Sereno
Keyword(s):  
User Interface ◽  
Factorial Design ◽  
Graphical User Interface ◽  
R Package ◽  
Psycholinguistic Research ◽  
Link Type ◽  
Control Current ◽  
Word Lists ◽  
And Control ◽  
Manipulation And Control

AbstractLexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/.

scholarly journals genBaRcode: a comprehensive R-package for genetic barcode analysis

2019 ◽  
Vol 36 (7) ◽  
pp. 2189-2194 ◽  
Author(s):  
Lars Thielecke ◽  
Kerstin Cornils ◽  
Ingmar Glauche
Keyword(s):  
User Interface ◽  
Next Generation Sequencing ◽  
Error Correction ◽  
Graphical User Interface ◽  
R Package ◽  
Next Generation ◽  
Analysis Strategies ◽  
Genetic Sequences ◽  
Reproducible Analysis ◽  
Generation Sequencing

Abstract Motivation Genetic barcodes have been established as an efficient method to trace clonal progeny of uniquely labeled cells by introducing artificial genetic sequences into the corresponding genomes. The assessment of those sequences relies on next generation sequencing and the subsequent analysis aiming to identify sequences of interest and correctly quantifying their abundance. Results We developed the genBaRcode package as a toolbox combining the flexibility of digesting next generation sequencing reads with or without a sophisticated barcode structure, with a variety of error-correction approaches and the availability of several types of visualization routines. Furthermore, a graphical user interface was incorporated to allow also less experienced R users package-based analyses. Finally, the provided tool is intended to bridge the gap between generating and analyzing barcode data and thereby supporting the establishment of standardized and reproducible analysis strategies. Availability and implementation The genBaRcode package is available at CRAN (https://cran.r-project.org/package=genBaRcode).

scholarly journals Varapp: A reactive web-application for variants filtering

2016 ◽  
Author(s):  
Julien Delafontaine ◽  
Alexandre Masselot ◽  
Robin Liechti ◽  
Dmitry Kuznetsov ◽  
Ioannis Xenarios ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Web Application ◽  
De Novo ◽  
Source Code ◽  
Regions Of Interest ◽  
Mendelian Diseases ◽  
Link Type ◽  
Large Sets ◽  
Front End

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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