geyser

Highly interactive & modular shiny app to explore three facets of RNA-Seq analysis: differential expression (DE), functional enrichment and pattern analysis. Several visualizations are implemented to provide a wide-ranging view of data sets. For DE analysis, we provide PCA plot, MA plot, Upset plot & heatmaps, in addition to a highly customizable gene plot. Seven different visualizations are available for functional enrichment analysis, and we also support gene pattern analysis. Genes of interest can be tracked across all modules using the gene scratchpad. In addition, carnation provides an integrated platform to manage multiple projects and user access that can be run on a central server to share with collaborators.

iSEEfier provides a set of functionality to quickly and intuitively create, inspect, and combine initial configuration objects. These can be conveniently passed in a straightforward manner to the function call to launch iSEE() with the specified configuration. This package currently works seamlessly with the sets of panels provided by the iSEE and iSEEu packages, but can be extended to accommodate the usage of any custom panel (e.g. from iSEEde, iSEEpathways, or any panel developed independently by the user).

This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.

This package contains diverse functionality to extend the usage of the iSEE package, including additional classes for the panels or modes facilitating the analysis of pathway analysis results. This package does not perform pathway analysis. Instead, it provides methods to embed precomputed pathway analysis results in a SummarizedExperiment object, in a manner that is compatible with interactive visualisation in iSEE applications.

flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.

miaDash provides a Graphical User Interface for the exploration of microbiome data. This way, no knowledge of programming is required to perform analyses. Datasets can be imported, manipulated, analysed and visualised with a user-friendly interface.