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Links to materials from tutorials and talks from useR 2019
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useR2019 materials

This file contains links to materials from all tutorials, some talks and a few posters from useR 2019. For talks, the official site now has links to most slides and soon also links to videos, so you'd probably want to look there first :)

Thanks to everyone who contributed to this repo, especially Sarah Musy (@musy_n) who shared many links and @gregrs-uk who helped fix some of my mistakes! Please feel free to make a pull request, add an issue, or tweet @s_owla :)

Note: I started this repo because I found materials from rstudio::conf 2019 that @kwbroman and others collected so helpful!


Tuesday: Morning Tutorials and Afternoon Tutorials


Wednesday: Keynotes, Applications 1, Applications 2, Bioinformatics 1, Data handling, Education, Models 1, Movement & transport, Multivariate analysis, Reproducibility, Shiny 1, Shiny 2 and Social science, marketing & business

Thursday: Keynotes, Bioinformatics 2, Biostatistics & epidemiology, Biostatistics & epidemiology 1, Communities & conferences, Data mining, Forecasting, Models 2, Numerical methods, Open science, education & community, Operations & data products, Programming 1, Programming 2, Spatial & time series, Spatial data & maps, Text mining, Visualisation and Workflow & development

Friday: Keynotes, Big/high dimensional data, Bioinformatics & biostatistics, Biostatistics & epidemiology 2, Contribution & collaboration, Methods & applications, Model deployment, Models & methods, Performance, Shiny & web, Switching to R and Time series data


Tuesday 9th July

Morning Tutorials

Afternoon Tutorials

Wednesday 10th July


Applications 1

Applications 2

Bioinformatics 1

Data handling


Models 1

Movement & transport

Multivariate analysis


Shiny 1

Shiny 2

Social science, marketing & business

Thursday 11th July


Bioinformatics 2

  • Interfacing R/Bioconductor with Hail, a Spark-based platform for genomics
    Michael Lawrence (@lawremi?)

  • iSEE: interactive and reproducible exploration and visualization of genomics data
    Federico Marini (@FedeBioinfo)

  • POMA: Shiny tool for targeted metabolomic data statistical analysis and visualization
    Pol Castellano-Escuder

Biostatistics & epidemiology

  • A Shiny Webapp for nutritional reformulation of food products according to French front-of-pack “Nutri-Score” label.
    Romane Poinsot

  • Using Shiny to track winter pressures in the UK National Health Service (NHS)
    Fiona Grimm

  • antibioticR: An R package to identify resistant populations in environmental bacteria
    Thomas Petzoldt

  • MR studies in R: how to use genetic information for identifying modifiable risk factors
    Daniela Mariosa

  • Streamlining complex analyses of in-vivo data with INVIVOLDA shiny application
    Volha Tryputsen

  • A shiny web application for disease mapping. Making easy the fit of spatio-temporal models.
    Aritz Adin

Biostatistics & epidemiology 1

  • Reproducible data science to support outbreak responses: experience from the North Kivu Ebola outbreak
    Thibaut Jombart

  • Advancing data analytics for field epidemiologists using R: the R4epis innovation project
    Zhian Kamvar

  • micemd: a smart multiple imputation R package for missing multilevel data
    Vincent Audigier

  • Facilitating external use with user-friendly interfaces: a health policy model case study
    Iryna Schlackow

  • genogeographer - a tool for ancestry informative markers
    Torben Tvedebrink

Communities & conferences

Data mining

  • Machine Learning with R: do it with a framework
    Eric Lecoutre (@EricLecoutre)

  • Building and Benchmarking Automatic Machine Learning Systems
    Erin Ledell

  • mlr3: A new modular framework for machine learning with R
    Michel Lang

  • mlr3pipelines: Machine Learning Pipelines as Graphs
    Bernd Bischl


Models 2

  • Using Rcpp* packages for easy and fast Gibbs sampling MCMC from within R
    Ghislain VieilledentJeanne Clément

  • A toolbox for fitting non-separable space-time log-Gaussian Cox models using R-INLA
    Elias Krainski

  • Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values
    Wei Jiang

  • REndo: An R Package to Address Endogeneity Without External Instrumental Variables
    Raluca Gui

  • Discovering the cause: Tools for structure learning in R
    Anne Helby Petersen

Numerical methods

Open science, education & community

  • Open-access software for research: beyond data analysis
    Saras Windecker

  • Teaching reproducible spatial analysis in R
    Angela Li

  • Use aRt to learn algorithms, math, and R
    William Chase

  • The evolution and importance of the R-Ladies São Paulo chapter in Brazil
    Beatriz Milz (@BeaMilz)

  • Building Active Community at Your Place
    Binod Jung Bogati

  • Scaling useR Communities with Engagement and Retention Models
    Eyitayo Alimi

Operations & data products

  • How a non-profit uses R for its daily operations
    Francois Michonneau (@fmic_)

  • rjenkins and rrundeck: Coordinating Continuous Integration and Delivery with R
    Daan Seynaeve

  • Advanced Git Integrations for Automating the Delivery of Reproducible Data Products in R
    Kelly Obriant

  • GitHub actions for R
    Verena HeldMax Held

Programming 1

Programming 2

  • Sustainable Package Development
    Tomas Kalibera

  • Typing R
    Elie Canonici Merle

  • nCompiler: C++ code-generation from R code
    Perry De Valpine

  • Mixed interactive debugging of R and native code with FastR and Vistual Studio Code
    Zbynek Slajchrt

Spatial & time series

  • R in the Air
    Enrico SpinielliTamara Pejovic

  • Measuring inequalities from space. Analysis of satellite raster images with R
    Piotr Wójcik

  • SILand: an R package for estimating the spatial influence of landscape
    Florence Carpentier

  • Spatio-temporal Analysis of Diabrotica Emergence
    Rodelyn Jaksons

  • Navigating spatial data management and analysis in Sustainable Fisheries using a combined R-Python approach
    Annette Scheffer

  • Dealing with the change of administrative divisions over time
    Kim Antunez (@robinlovelace)

  • persephone, seasonal adjustment with an object-oriented wrapper for RJDmetra
    Gregor De Cillia

Spatial data & maps

Text mining

  • {polite} - web etiquette for R users
    Dmytro Perepolkin (@dmi3k)

  • The R Package sentometrics to Compute, Aggregate and Predict with Textual Sentiment; package
    Samuel Borms

  • BibliographeR : a set of tools to help your bibliographic research; package; app
    Cécile Sauder (@cecilesauder) and Jean Delmotte (@DrStagiaire)

  • ggwordcloud: a word cloud geometry for ggplot2; package
    Erwan Le Pennec

  • Die Nutella oder Das Nutella? Grammatical Gender Prediction of German Nouns
    Chung-Hong Chan (@chainsawriot)

  • Implementing a Classification and Filtering App for Multilingual Facebook Comments – A Use Case Of Data For Good with R
    Johannes Müller (@jj_mllr) from CorrelAid (@CorrelAid)

  • queryMed: Linking pharmacological and medical knowledge using semantic Web technologies; package
    Nolwenn Le Meur (@nlemeur)


Workflow & development

Friday 12th July


  • Tools for Model-Based Clustering in R; package
    Bettina Grün

  • 'AI for Good' in the R and Python ecosystems; video
    Julien Cornebise (@JCornebise)

Big/high dimensional data

Bioinformatics & biostatistics

  • rGSAn: a R package dedicated to the gene set analysis using semantic similarity measures.
    Aarón Ayllón-BenítezPatricia Thebault

  • Pathway-VisualiseR: An Interactive Web Application for Visualising Gene Networks
    Goknur GinerAlexandra Garnham

  • Compiling a global database of sapflow measurements with R: Workflow and tools for the SAPFLUXNET database
    Víctor Granda

  • Bayesian sequential integration within a preclinical PK/PD modeling framework using rstan package: Lessons learned
    Fabiola La Gamba

  • VICI: a Shiny app for accurate estimation of Vaccine Induced Cellular Immunogenicity with bivariate modeling
    Boris Hejblum

  • Tools for 3D/4D interactive visualisation of cells and biological tissue
    Marion Louveaux

  • Analysis of laboratory test requests in a university hospital: A Shiny App for association analysis as a demand management tool
    Deniz Topcu

Biostatistics & epidemiology 2

  • Implementation and analysis design of an adaptive-outcome trial in R
    Alessio Crippa

  • Advances in dose-response analysis
    Christian RitzJens C. Streibig

  • The next generation of the survival package
    Terry Therneau

  • A flexible approach to time-to-event data analysis using case-base sampling
    Jesse Islam

  • The R package mixmeta: an extended mixed-effects framework for meta-analysis
    Antonio Gasparrini

Contribution & collaboration

  • How to win friends and write an open-source book
    Jakub Nowosad (@jakub_nowosad) and Robin Lovelace (@robinlovelace)

  • Making sense of CRAN: Package and collaboration networks
    Ioannis Kosmidis

  • RWsearch: a package for CRAN users and task view maintainers
    Patrice Kiener

  • Translating datasets using "datalang": the development of "datos" package for the R4DS Spanish translation
    Riva Quiroga

  • R Consortium Working Groups
    Joseph Rickert

Methods & applications

Model deployment

Models & methods

  • Adjusting reviewer scores for a fairer assessment via multi-faceted Rasch modelling
    Caterina Constantinescu

  • Penalized regressions to study multivariate linear models : the VariSel package.
    Marie Perrot-Dockès

  • Maximum spacing estimation, a new method in fitdistrplus
    Christophe Dutang

  • rama: an R interface to the GAMA agent-based modeling platform
    Marc Choisy

  • RcppGreedySetCover: Scalable Set Cover
    Kaeding Matthias

  • The GPareto and GPGame packages for multi and many objective Bayesian optimization
    Mickaël Binois


Shiny & web

Switching to R

Time series data


R package development using Gitlab CI/CD
Jean-Francois Rey (@jfrey_official)

Shiny-Powered e-Learning Platform to Teach Calcium and Phosphate Homeostasis
David Granjon (@divadnojnarg)

Using Fridges to Balance the Electricity Grid
Ellen Webborn (@EllenWebborn)

Quantifying the impact of tree choice in metagenomics differential abundance studies with R Antoine Bichat (@_abichat)

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