shiny

Helm chart for Shinyproxy

Birds of Havel shiny app. https://havel.fly.dev/

Trimming, alignment and variant identification tool. Made to help professional make a quick variant identification through an easy to follow user interface developed in R with the Shiny framework.

Shiny Dashboard zur Visualisierung der Beringungs- und Beobachtungsdaten der Greifswalder Oie. https://vereinjordsand.shinyapps.io/goie/

An R-Shiny application implementing a method of sexing the human os coxae based on logistic regressions and Bruzek's nonmetric traits doi:10.1002/ajpa.23855.

R package providing logging to Shiny apps and other R scripts.

Shiny Server packaged in a Docker container

"Cloud container data analytics, statistical modeling, and machine learning on distributed databases". "A free opensource alternative to SPSS, SAS, MATLAB, PowerBI, Tableau and Alteryx". Runs on Linux, Windows, MacOS, and in the cloud via containers.

Allows the transformation of a Bam file into a Bigwig file. The app is based on "bamcoverage" of the Deeptools tool.

Allows table cleaning containing RNAseq data (number of counts per genes).

Shiny is becoming a popular publishing service, unfortunately, not every application can be deployed on servers. This tutorial demonstrates a simple means by which to deploy a shiny app to desktop.

An R-Shiny application for the exhaustive cartography and user-friendly statistical analysis of long bone diaphyses. https://doi.org/10.1002/ajpa.23835

Exemples of my work building web applications and interactive dashboards with Shiny

Shiny-based web app that can be used to browse Halias (Hanko Bird Observatory) observations

Interactive time series visualization for the data scientist.

Tutorial 1 for R shiny package and git

Ejemplo de uso de Shiny para Rstudio y R

Aplicativo Shiny (RStudio) para coletores botânicos, taxonomistas e ecólogos organizarem seus dados brutos anotados em cadernetas, aparelhos de GPS, máquinas fotográficas.

King County House Sales

Slides from my R/Pharma 2018 presentation: Developing Powerful Shiny Applications in an Enterprise Environment: Best Practices and Lessons Learned. https://rpodcast.gitlab.io/rpharma2018