scholarly journals feedrand animalnexus.ca: A paired R package and user-friendly Web application for transforming and visualizing animal movement data from static stations

2017 ◽  
Vol 7 (19) ◽  
pp. 7884-7896 ◽  
Author(s):  
Stefanie E. LaZerte ◽  
Matthew W. Reudink ◽  
Ken A. Otter ◽  
Jackson Kusack ◽  
Jacob M. Bailey ◽  
...  
Keyword(s):  
Web Application ◽  
Animal Movement ◽  
R Package ◽  
Movement Data ◽  
User Friendly

scholarly journals DiscoRhythm: an easy-to-use web application and R package for discovering rhythmicity

2019 ◽  
Author(s):  
Matthew Carlucci ◽  
Algimantas Kriščiūnas ◽  
Haohan Li ◽  
Povilas Gibas ◽  
Karolis Koncevičius ◽  
...  
Keyword(s):  
Web Application ◽  
Statistical Significance ◽  
R Package ◽  
Biological Data ◽  
Supplementary Information ◽  
Statistical Knowledge ◽  
Health And Disease ◽  
Phase Amplitude ◽  
Almost All ◽  
User Friendly

Abstract Motivation Biological rhythmicity is fundamental to almost all organisms on Earth and plays a key role in health and disease. Identification of oscillating signals could lead to novel biological insights, yet its investigation is impeded by the extensive computational and statistical knowledge required to perform such analysis. Results To address this issue, we present DiscoRhythm (Discovering Rhythmicity), a user-friendly application for characterizing rhythmicity in temporal biological data. DiscoRhythm is available as a web application or an R/Bioconductor package for estimating phase, amplitude, and statistical significance using four popular approaches to rhythm detection (Cosinor, JTK Cycle, ARSER, and Lomb-Scargle). We optimized these algorithms for speed, improving their execution times up to 30-fold to enable rapid analysis of -omic-scale datasets in real-time. Informative visualizations, interactive modules for quality control, dimensionality reduction, periodicity profiling, and incorporation of experimental replicates make DiscoRhythm a thorough toolkit for analyzing rhythmicity. Availability and Implementation The DiscoRhythm R package is available on Bioconductor (https://bioconductor.org/packages/DiscoRhythm), with source code available on GitHub (https://github.com/matthewcarlucci/DiscoRhythm) under a GPL-3 license. The web application is securely deployed over HTTPS (https://disco.camh.ca) and is freely available for use worldwide. Local instances of the DiscoRhythm web application can be created using the R package or by deploying the publicly available Docker container (https://hub.docker.com/r/mcarlucci/discorhythm). Supplementary information Supplementary data are available at Bioinformatics online.

MetENP/MetENPWeb: An R package and web application for metabolomics enrichment and pathway analysis in Metabolomics Workbench

2020 ◽  
Author(s):  
Kumari Sonal Choudhary ◽  
Eoin Fahy ◽  
Kevin Coakley ◽  
Manish Sud ◽  
Mano R Maurya ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Web Application ◽  
Enrichment Analysis ◽  
R Package ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Kegg Pathways ◽  
Link Type ◽  
Species Specific ◽  
User Friendly

ABSTRACTWith the advent of high throughput mass spectrometric methods, metabolomics has emerged as an essential area of research in biomedicine with the potential to provide deep biological insights into normal and diseased functions in physiology. However, to achieve the potential offered by metabolomics measures, there is a need for biologist-friendly integrative analysis tools that can transform data into mechanisms that relate to phenotypes. Here, we describe MetENP, an R package, and a user-friendly web application deployed at the Metabolomics Workbench site extending the metabolomics enrichment analysis to include species-specific pathway analysis, pathway enrichment scores, gene-enzyme information, and enzymatic activities of the significantly altered metabolites. MetENP provides a highly customizable workflow through various user-specified options and includes support for all metabolite species with available KEGG pathways. MetENPweb is a web application for calculating metabolite and pathway enrichment analysis.Availability and ImplementationThe MetENP package is freely available from Metabolomics Workbench GitHub: (https://github.com/metabolomicsworkbench/MetENP), the web application, is freely available at (https://www.metabolomicsworkbench.org/data/analyze.php)

Guidelines to understand and compute the number needed to treat

2021 ◽  
pp. ebmental-2020-300232
Author(s):  
Valentin Vancak ◽  
Yair Goldberg ◽  
Stephen Z Levine
Keyword(s):  
Web Application ◽  
Cox Regression ◽  
R Package ◽  
Successful Outcome ◽  
Number Needed To Treat ◽  
Explanatory Variables ◽  
Kaplan Meier ◽  
Number Of Patients ◽  
Copy And Paste ◽  
User Friendly

ObjectiveWe aim to explain the unadjusted, adjusted and marginal number needed to treat (NNT) and provide software for clinicians to compute them.MethodsThe NNT is an efficacy index that is commonly used in randomised clinical trials. The NNT is the average number of patients needed to treat to obtain one successful outcome (ie, response) due to treatment. We developed the nntcalc R package for desktop use and extended it to a user-friendly web application. We provided users with a user-friendly step-by-step guide. The application calculates the NNT for various models with and without explanatory variables. The implemented models for the adjusted NNT are linear regression and analysis of variance (ANOVA), logistic regression, Kaplan-Meier and Cox regression. If no explanatory variables are available, one can compute the unadjusted Laupacis et al’s NNT, Kraemer and Kupfer’s NNT and the Furukawa and Leucht’s NNT. All NNT estimators are computed with their associated appropriate 95% confidence intervals. All calculations are in R and are replicable.ResultsThe application provides the user with an easy-to-use web application to compute the NNT in different settings and models. We illustrate the use of the application from examples in schizophrenia research based on the Positive and Negative Syndrome Scale. The application is available from https://nntcalc.iem.technion.ac.il. The output is given in a journal compatible text format, which users can copy and paste or download in a comma-separated values format.ConclusionThis application will help researchers and clinicians assess the efficacy of treatment and consequently improve the quality and accuracy of decisions.

scholarly journals Correlation AnalyzeR: functional predictions from gene co-expression correlations

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Henry E. Miller ◽  
Alexander J. R. Bishop
Keyword(s):  
Web Application ◽  
Bone Cancer ◽  
R Package ◽  
Limited Range ◽  
Web Interface ◽  
Generating Functional ◽  
Link Type ◽  
Genome Wide ◽  
User Friendly

Abstract Background Co-expression correlations provide the ability to predict gene functionality within specific biological contexts, such as different tissue and disease conditions. However, current gene co-expression databases generally do not consider biological context. In addition, these tools often implement a limited range of unsophisticated analysis approaches, diminishing their utility for exploring gene functionality and gene relationships. Furthermore, they typically do not provide the summary visualizations necessary to communicate these results, posing a significant barrier to their utilization by biologists without computational skills. Results We present Correlation AnalyzeR, a user-friendly web interface for exploring co-expression correlations and predicting gene functions, gene–gene relationships, and gene set topology. Correlation AnalyzeR provides flexible access to its database of tissue and disease-specific (cancer vs normal) genome-wide co-expression correlations, and it also implements a suite of sophisticated computational tools for generating functional predictions with user-friendly visualizations. In the usage example provided here, we explore the role of BRCA1-NRF2 interplay in the context of bone cancer, demonstrating how Correlation AnalyzeR can be effectively implemented to generate and support novel hypotheses. Conclusions Correlation AnalyzeR facilitates the exploration of poorly characterized genes and gene relationships to reveal novel biological insights. The database and all analysis methods can be accessed as a web application at https://gccri.bishop-lab.uthscsa.edu/correlation-analyzer/ and as a standalone R package at https://github.com/Bishop-Laboratory/correlationAnalyzeR.

scholarly journals A USER-FRIENDLY REMOTE-SENSING WEB-PLATFORM FOR BIODIVERSITY CONSERVATION AND MANAGEMENT IN PROTECTED AREAS

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 441-446
Author(s):  
R. O. Chávez ◽  
J. A. Lastra ◽  
D. Valencia ◽  
I. Díaz-Hormazábal
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Confidence Intervals ◽  
Web Application ◽  
Vegetation Index ◽  
R Package ◽  
Severe Drought ◽  
User Friendly ◽  
Web Platform ◽  
Conservation And Management

Abstract. The Chilean SNASPE is a complex network of 104 protected areas covering 18.5 million hectares of continental and insular Chile in South America. The geographical complexity and high biodiversity of the SNASPE make difficult to develop a unified monitoring system for conservation and management. In this contribution, we introduce a novel and remote-sensing web-platform for monitoring SNASPE units based completely in open acces data and software. The platform was designed in close cooperation with the Chilean forest service CONAF in order to make it applicable to the whole SNASPE. Following the framework of the Group on Earth Observation - Biodiversity Observation Network (GEO-BON), we used the Essential Biodiversity Variable (EBV) Phenology and MODIS Enhanced Vegetation Index (EVI) data to detect in near-real-time anomalies from the normal annual phenological cycle of vegetation. The platform is based on a flexible non-parametric probabilistic algorithm (the “npphen” R package) capable to reconstruct any type of leaf phenology and to quantify its inter-annual variation by means of confidence intervals around the most probable annual curve. Phenological anomalies are then calculated as a deviation from the expected annual cycle and judged based on their location within the confidence intervals. Anomalies located above 95% confidence interval trigger a “red alert” which is displayed on the web application as soon as the MODIS data become available. This user-friendly platform was implemented in the La Campana National Park giving early alerts of a severe drought in 2019, warning Conaf to implement actions to protect the park from potential wild fires.

scholarly journals Exploratory movement analysis and report building with R package stmove

2019 ◽  
Author(s):  
Dana P. Seidel ◽  
Eric R. Dougherty ◽  
Wayne M. Getz
Keyword(s):  
Best Practice ◽  
Animal Movement ◽  
Movement Ecology ◽  
Movement Analysis ◽  
R Package ◽  
Movement Data ◽  
Starting Point ◽  
Terrestrial Movement ◽  
Using Data ◽  
Analytical Tools

AbstractBackgroundAs GPS tags and data loggers have become lighter, cheaper, and longer-lasting, there has been a growing influx of data on animal movement. Simultaneously, methods of analyses and software to apply such methods to movement data have expanded dramatically. Even so, for many interdisciplinary researchers and managers without familiarity with the field of movement ecology and the open-source tools that have been developed, the analysis of movement data has remained an overwhelming challenge.DescriptionHere we present stmove, an R package designed to take individual relocation data and generate a visually rich report containing a set of preliminary results that ecologists and managers can use to guide further exploration of their data. Not only does this package make report building and exploratory data analysis (EDA) simple for users who may not be familiar with the extent of available analytical tools, but it sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data.ResultsUsing data from African elephants (Loxodonta africana) collected in southern Africa, we demonstrate stmove’s report building function through the main analyses included: path visualization, primary statistic calculation, summary in space and time, and space-use construction.ConclusionsThe stmove package provides consistency and increased accessibility to managers and researchers who are interested in movement analysis but who may be unfamiliar with the full scope of movement packages and analytical tools. If widely adopted, the package will promote comparability of results across movement ecology studies.

scholarly journals PDF Data Extractor (PDE) - A Free Web Application and R Package Allowing the Extraction of Tables from Portable Document Format (PDF) Files and High-Throughput Keyword Searches of Full-Text Articles

2021 ◽  
Author(s):  
Erik Stricker ◽  
Michael E Scheurer
Keyword(s):  
Full Text ◽  
Web Application ◽  
Scientific Literature ◽  
Portable Document Format ◽  
R Package ◽  
Literature Analysis ◽  
Full Text Article ◽  
Literature Reviews ◽  
User Friendly ◽  
Keyword Searches

The PDF Data Extractor (PDE) R package is designed to perform comprehensive literature reviews for scientists at any stage in a user-friendly way. The PDE_analyzer_i() function permits the user to filter and search thousands of scientific articles using a simple user interface, requiring no bioinformatics skills. In the additional PDE_reader_i() interface, the user can then quickly browse the sentences with detected keywords, open the full-text article, when required, and convert tables conveniently from PDF files to Excel sheets (pdf2table). Specific features of the literature analysis include the adaptability of analysis parameters and the detection of abbreviations of search words in articles. In this article, we demonstrate and exemplify how the PDE package allows the user-friendly, efficient, and automated extraction of meta-data from full-text articles, which can aid in summarizing the existing literature on any topic of interest. As such, we recommend the use of the PDE package as the first step in conducting an extensive review of the scientific literature. The PDE package is available from the Comprehensive R Archive Network at https://CRAN.R-project.org/package=PDE.

scholarly journals EpiDISH web server: Epigenetic Dissection of Intra-Sample-Heterogeneity with online GUI

2019 ◽  
Author(s):  
Shijie C Zheng ◽  
Charles E Breeze ◽  
Stephan Beck ◽  
Danyue Dong ◽  
Tianyu Zhu ◽  
...  
Keyword(s):  
Web Application ◽  
Association Studies ◽  
Web Server ◽  
Cell Types ◽  
R Package ◽  
Cell Type ◽  
Cell Type Composition ◽  
Type Composition ◽  
User Friendly ◽  
Sample Heterogeneity

Abstract Summary It is well recognized that cell-type heterogeneity hampers the interpretation of Epigenome-Wide Association Studies (EWAS). Many tools have emerged to address this issue, including several R/Bioconductor packages that infer cell-type composition. Here we present a web application for cell-type deconvolution, which offers the functionality of our EpiDISH Bioconductor/R package in a user-friendly GUI environment. Users can upload their data to infer cell-type composition and differentially methylated cytosines in individual cell-types (DMCTs) for a range of different tissues. Availability and implementation EpiDISH web server is implemented with Shiny in R, and is freely available at https://www.biosino.org/EpiDISH/.

scholarly journals scAgeCom: a murine atlas of age-related changes in intercellular communication inferred with the package scDiffCom

2021 ◽  
Author(s):  
Cyril Lagger ◽  
Eugen Ursu ◽  
Anais Equey ◽  
Roberto A Avelar ◽  
Angela O Pisco ◽  
...  
Keyword(s):  
Single Cell ◽  
Intercellular Communication ◽  
Web Application ◽  
R Package ◽  
Cell Type ◽  
Communication Analysis ◽  
Age Related ◽  
Mouse Tissues ◽  
Transcriptomics Data ◽  
User Friendly

Dysregulation of intercellular communication is a well-established hallmark of aging. To better understand how this process contributes to the aging phenotype, we built scAgeCom, a comprehensive atlas presenting how cell-type to cell-type interactions vary with age in 23 mouse tissues. We first created an R package, scDiffCom, designed to perform differential intercellular communication analysis between two conditions of interest in any mouse or human single-cell RNA-seq dataset. The package relies on its own list of curated ligand-receptor interactions compiled from seven established studies. We applied this tool to single-cell transcriptomics data from the Tabula Muris Senis consortium and the Calico murine aging cell atlas. All the results can be accessed online, using a user-friendly, interactive web application (https://scagecom.org). The most widespread changes we observed include upregulation of immune system processes, inflammation and lipid metabolism, and downregulation of extracellular matrix organization, growth, development and angiogenesis. More specific interpretations are also provided.

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