webMCP-counter: a web interface for transcriptomics-based quantification of immune and stromal cells in heterogeneous human or murine samples

Correlation AnalyzeR: functional predictions from gene co-expression correlations

BMC Bioinformatics ◽

10.1186/s12859-021-04130-7 ◽

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.

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see: An R Package for Visualizing Statistical Models

10.31234/osf.io/m4uax ◽

2021 ◽

Author(s):

Daniel Lüdecke ◽

Indrajeet Patil ◽

Mattan S. Ben-Shachar ◽

Brenton M. Wiernik ◽

Philip Waggoner ◽

...

Keyword(s):

Programming Language ◽

Statistical Models ◽

R Package ◽

Model Parameters ◽

R Programming Language ◽

R Packages ◽

R Programming ◽

And Performance ◽

Performance Diagnostics ◽

Scientific Reporting

The see package is embedded in the easystats ecosystem, a collection of R packages that operate in synergy to provide a consistent and intuitive syntax when working with statistical models in the R programming language (R Core Team, 2021). Most easystats packages return comprehensive numeric summaries of model parameters and performance. The see package complements these numeric summaries with a host of functions and tools to produce a range of publication-ready visualizations for model parameters, predictions, and performance diagnostics. As a core pillar of easystats, the see package helps users to utilize visualization for more informative, communicable, and well-rounded scientific reporting.

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STATISTICAL CALCULATOR

10.31227/osf.io/jy56w ◽

2018 ◽

Author(s):

Prana Ugiana Gio ◽

Rezzy Eko Caraka

Keyword(s):

R Package ◽

Process Data ◽

Web Based ◽

Application Program ◽

R Programming Language ◽

Statistical Application ◽

R Shiny ◽

R Packages ◽

R Programming ◽

Mozilla Firefox

STATCAL is an free statistical application program that is designed using R programming language, in RStudio. STATCAL uses various R packages to perform graphical and statistical analysis. STATCAL is a web-based statistical application program. It means that STATCAL uses a browser, such as Google Chrome, Mozilla Firefox, etc, as a place or media to process data. R shiny package is a main package in STATCAL. R shiny package is an R package that can be used to create an interactive web-based application. STATCAL is created by Prana Ugiana Gio and Rezzy Eko Caraka on 2017.

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Introducing bdclean: a user friendly biodiversity data cleaning pipeline

Biodiversity Information Science and Standards ◽

10.3897/biss.2.25564 ◽

2018 ◽

Vol 2 ◽

pp. e25564

Author(s):

Tomer Gueta ◽

Vijay Barve ◽

Thiloshon Nagarajah ◽

Ashwin Agrawal ◽

Yohay Carmel

Keyword(s):

Data Cleaning ◽

Control Process ◽

R Package ◽

Modular Approach ◽

Data Validation ◽

Biodiversity Data ◽

Quality Control Process ◽

Cleaning Procedures ◽

R Packages ◽

User Friendly

A new R package for biodiversity data cleaning, 'bdclean', was initiated in the Google Summer of Code (GSoC) 2017 and is available on github. Several R packages have great data validation and cleaning functions, but 'bdclean' provides features to manage a complete pipeline for biodiversity data cleaning; from data quality explorations, to cleaning procedures and reporting. Users are able go through the quality control process in a very structured, intuitive, and effective way. A modular approach to data cleaning functionality should make this package extensible for many biodiversity data cleaning needs. Under GSoC 2018, 'bdclean' will go through a comprehensive upgrade. New features will be highlighted in the demonstration.

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CrosstalkNet: mining large-scale bipartite co-expression networks to characterize epi-stroma crosstalk

10.1101/102848 ◽

2017 ◽

Author(s):

Venkata Manem ◽

George Adam ◽

Tina Gruosso ◽

Mathieu Gigoux ◽

Nicholas Bertos ◽

...

Keyword(s):

Stromal Cells ◽

Large Scale ◽

Network Visualization ◽

Visualization Tool ◽

Biological Processes ◽

Web Based ◽

Link Type ◽

A Cell ◽

Large Scale Networks ◽

User Friendly

ABSTRACTBackground:Over the last several years, we have witnessed the metamorphosis of network biology from being a mere representation of molecular interactions to models enabling inference of complex biological processes. Networks provide promising tools to elucidate intercellular interactions that contribute to the functioning of key biological pathways in a cell. However, the exploration of these large-scale networks remains a challenge due to their high-dimensionality.Results:CrosstalkNet is a user friendly, web-based network visualization tool to retrieve and mine interactions in large-scale bipartite co-expression networks. In this study, we discuss the use of gene co-expression networks to explore the rewiring of interactions between tumor epithelial and stromal cells. We show how CrosstalkNet can be used to efficiently visualize, mine, and interpret large co-expression networks representing the crosstalk occurring between the tumour and its microenvironment.Conclusion:CrosstalkNet serves as a tool to assist biologists and clinicians in exploring complex, large interaction graphs to obtain insights into the biological processes that govern the tumor epithelial-stromal crosstalk. A comprehensive tutorial along with case studies are provided with the application.Availability:The web-based application is available at the following location: http://epistroma.pmgenomics.ca/app/. The code is open-source and freely available from http://github.com/bhklab/EpiStroma-webapp.Contact:[email protected]

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RCy3: Network biology using Cytoscape from within R

F1000Research ◽

10.12688/f1000research.20887.3 ◽

2019 ◽

Vol 8 ◽

pp. 1774 ◽

Cited By ~ 1

Author(s):

Julia A. Gustavsen ◽

Shraddha Pai ◽

Ruth Isserlin ◽

Barry Demchak ◽

Alexander R. Pico

Keyword(s):

Shortest Path ◽

Future Development ◽

Enrichment Analysis ◽

Network Biology ◽

R Package ◽

Programming Environment ◽

R Packages ◽

R Programming ◽

Shortest Path Algorithms ◽

Rest Api

RCy3 is an R package in Bioconductor that communicates with Cytoscape via its REST API, providing access to the full feature set of Cytoscape from within the R programming environment. RCy3 has been redesigned to streamline its usage and future development as part of a broader Cytoscape Automation effort. Over 100 new functions have been added, including dozens of helper functions specifically for intuitive data overlay operations. Over 40 Cytoscape apps have implemented automation support so far, making hundreds of additional operations accessible via RCy3. Two-way conversion with networks from \textit{igraph} and \textit{graph} ensures interoperability with existing network biology workflows and dozens of other Bioconductor packages. These capabilities are demonstrated in a series of use cases involving public databases, enrichment analysis pipelines, shortest path algorithms and more. With RCy3, bioinformaticians will be able to quickly deliver reproducible network biology workflows as integrations of Cytoscape functions, complex custom analyses and other R packages.

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

10.1101/2020.11.20.391912 ◽

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)

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Progress in the R ecosystem for representing and handling spatial data

Journal of Geographical Systems ◽

10.1007/s10109-020-00336-0 ◽

2020 ◽

Cited By ~ 1

Author(s):

Roger S. Bivand

Keyword(s):

New York ◽

Data Analysis ◽

Open Source ◽

Spatial Data ◽

Spatial Data Analysis ◽

Data Handling ◽

Good Match ◽

R Programming Language ◽

R Packages ◽

R Programming

Abstract Twenty years have passed since Bivand and Gebhardt (J Geogr Syst 2(3):307–317, 2000. 10.1007/PL00011460) indicated that there was a good match between the then nascent open-source R programming language and environment and the needs of researchers analysing spatial data. Recalling the development of classes for spatial data presented in book form in Bivand et al. (Applied spatial data analysis with R. Springer, New York, 2008, Applied spatial data analysis with R, 2nd edn. Springer, New York, 2013), it is important to present the progress now occurring in representation of spatial data, and possible consequences for spatial data handling and the statistical analysis of spatial data. Beyond this, it is imperative to discuss the relationships between R-spatial software and the larger open-source geospatial software community on whose work R packages crucially depend.

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SpatialDB: a database for spatially resolved transcriptomes

Nucleic Acids Research ◽

10.1093/nar/gkz934 ◽

2019 ◽

Cited By ~ 3

Author(s):

Zhen Fan ◽

Runsheng Chen ◽

Xiaowei Chen

Keyword(s):

Spatial Organization ◽

Expression Patterns ◽

Functional Enrichment ◽

Web Interface ◽

Current Version ◽

Transcriptomic Data ◽

Spatially Resolved ◽

User Friendly ◽

New Strategies

Abstract Spatially resolved transcriptomic techniques allow the characterization of spatial organization of cells in tissues, which revolutionize the studies of tissue function and disease pathology. New strategies for detecting spatial gene expression patterns are emerging, and spatially resolved transcriptomic data are accumulating rapidly. However, it is not convenient for biologists to exploit these data due to the diversity of strategies and complexity in data analysis. Here, we present SpatialDB, the first manually curated database for spatially resolved transcriptomic techniques and datasets. The current version of SpatialDB contains 24 datasets (305 sub-datasets) from 5 species generated by 8 spatially resolved transcriptomic techniques. SpatialDB provides a user-friendly web interface for visualization and comparison of spatially resolved transcriptomic data. To further explore these data, SpatialDB also provides spatially variable genes and their functional enrichment annotation. SpatialDB offers a repository for research community to investigate the spatial cellular structure of tissues, and may bring new insights into understanding the cellular microenvironment in disease. SpatialDB is freely available at https://www.spatialomics.org/SpatialDB.

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RCy3: Network biology using Cytoscape from within R

F1000Research ◽

10.12688/f1000research.20887.2 ◽

2019 ◽

Vol 8 ◽

pp. 1774 ◽

Cited By ~ 13

Author(s):

Julia A. Gustavsen ◽

Shraddha Pai ◽

Ruth Isserlin ◽

Barry Demchak ◽

Alexander R. Pico

Keyword(s):

Shortest Path ◽

Future Development ◽

Enrichment Analysis ◽

Network Biology ◽

R Package ◽

Programming Environment ◽

R Packages ◽

R Programming ◽

Shortest Path Algorithms ◽

Rest Api

RCy3 is an R package in Bioconductor that communicates with Cytoscape via its REST API, providing access to the full feature set of Cytoscape from within the R programming environment. RCy3 has been redesigned to streamline its usage and future development as part of a broader Cytoscape Automation effort. Over 100 new functions have been added, including dozens of helper functions specifically for intuitive data overlay operations. Over 40 Cytoscape apps have implemented automation support so far, making hundreds of additional operations accessible via RCy3. Two-way conversion with networks from \textit{igraph} and \textit{graph} ensures interoperability with existing network biology workflows and dozens of other Bioconductor packages. These capabilities are demonstrated in a series of use cases involving public databases, enrichment analysis pipelines, shortest path algorithms and more. With RCy3, bioinformaticians will be able to quickly deliver reproducible network biology workflows as integrations of Cytoscape functions, complex custom analyses and other R packages.

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