9h-12h30

Adrian Zetner, Canada Public Health Agency of Winnipeg

Introduction to R (EN)

This workshop will introduce the R programming language in an accessible manner to those with little to no experience with programming. A brief primer on all things R will be followed with interactive exercises and teaching of foundational concepts. The workshop will begin with a look at the R ecosystem including CRAN, RStudio, and finding / installing packages. We will move into guided exercises to introduce you to two important classes of data in R: vectors and data frames. Armed with this knowledge we will look into functional programming and scripting. After this course you will be well equipped to use R at a basic level and continue learning more advanced concepts.
To participate please bring a laptop with the latest versions of R and RStudio installed. No pre-installed packages will be required.

9h-12h30

Julie Faure-Lacroix, Calcul Québec

Introduction à ggplot2 (FR)

Avoir la capacité de produire des graphiques élégants et pertinents est un atout essentiel en recherche. Dans cette formation, nous aborderons les bonnes pratiques en visualisation de données ainsi que les possibilités offertes par le package ggplot2. Il s’agit d’un package basé sur la grammar of graphics et qui permet de créer un vaste éventail de graphiques, des plus simples aux plus complexes. Nous aborderons entre autres les concepts de couches (layers), les propriétés graphiques (aesthetics), les éléments graphiques (geometries), ainsi que les statistiques représentées graphiquement (statistics). Cette formation vous permettra de choisir un type de visualisation correspondant aux données dont vous disposez et ensuite le représenter graphiquement de façon rapide et flexible.

[ggplot2 et dplyr seront les seuls packages nécessaires pour l’atelier, mais il est possible d’installer directement tidyverse si vous le souhaitez].

9h-12h30

Hector Galvez, McGill

Introduction à R (FR)

Dans cet atelier, les participants vont apprendre les concepts de base du langage R et compléter de courts exercices de programmation. Le matériel couvert inclut l’environment R, R studio et CRAN, les forces et faiblesses de R démontrées par des exemples d’usages appropriés, ainsi que les classes et éléments de base du langage tels que data frame, vector, list, character, integer, et factor. Pour la partie interactive, les participants apprendront à installer des packages, importer et exporter des données, et manipuler des tableaux et vecteurs. Finalement, une démonstration de différentes façons de programmer en R tel que les R markdown et reports donneront un aperçu des potentiels de R.
L’atelier s’adresse aux débutant n’ayant jamais programmé en R, ou autre langage, et a pour objectif de fournir les concepts de base nécessaires à un apprentissage autonome continu. Les participants devront apporter leur ordinateur et avoir installé R et R studio au préalable.

13h30-17h

Vahid Partovi Nia, Huawei Technologies, Ecole Polytechnique de Montreal

Introductory Machine Learning (EN)

The aim of this workshop is to introduce some elementary R skills such as data loading, data pre-processing, and data visualization. We will practice some machine learning libraries to execute several supervised, unsupervised, and semi-supervised learning algorithms. Please install R and packages: MASS, scatterplot3d, e1071, neuralnet, deepnet
Machine learning requires a wrap of several skills, such as coding, optimization, statistics, and data analysis. This set of skills facilitates extraction of knowledge from large volumes of structured or unstructured data. It is a subfield of artificial intelligence with the purpose of discovering the underlying pattern of data through predictive modeling. The ultimate goal is to adopt data preprocessing, statistics, and black box predictive algorithms in order to draw conclusions and take (automatic) actions from (large amount of) data.

13h30-17h

Wayne Oldford, University of Waterloo

Intro to loon, an extendible toolkit for exploratory visualization and data analysis (EN)

Loon is an interactive visualization toolkit for analysts/users/developers engaged in open-ended, creative, and possibly unscripted data exploration. Loon‘s base set of plots include scatterplots, histograms, barplots, parallel and radial axes plots, graph structures, and any combination of these. Designed for interactive exploratory data analysis, loon plots can be horizontally/vertically panned, horizontally/vertically zoomed, and have plot elements linked to one another to effect such coordinated display behaviour as the selection of points, brushing, etc. Beyond a standard suite, loon scatterplots allow a wide variety of point glyphs including serial axes glyphs, text strings, or any custom designed image. Point glyphs may be interactively changed (e.g. colours, shape, size, image, visibility, even location) and functions written which react to any of these changes (thus permitting new interactive possibilities). Scatterplots are also layered, where each layer may contain any number of graphic elements (e.g. lines, circles, polygons, text, etc.), and layers may be made invisible or moved up or down the rendering stack. Common uses of layers include maps and display of fitted functions; layered elements are objects which can also be made to react to arbitrary changes in the display. A “loon inspector” provides a central control panel shared by all plots but which adapts to whichever is the active plot.

In this tutorial, participants will become familiar with loon’s functionality through a series of examples and hands-on exercises. These will cover a wide spectrum of applications beginning with data analysis, including high-dimensional exploratory data analysis, methodological exploration for the classroom or research, as well as exploratory prototyping of new interactive visualizations. To get a full sense of loon’s power, it is highly recommended that participants come with a laptop having installed loon (from CRAN) prior to the tutorial.

13h30-17h

François Lefebvre and Emmanuel Gonzalez, Canadian Centre for Computational Genomics

R pour la bioinformatique (FR)

R est sans contredit l’un des langages de programmation parmi les plus utiles au traitement et à l’analyse de données en sciences biologiques. Cet atelier offrira un survol pratique de différents types de données avec lesquelles travaille un bio-informaticien, ainsi que des packages R les plus couramment employés pour leur analyse. Seront abordés: intégrations de séquences biologiques (genomes, tumeurs, virus, bactéries), manipulation d’intervalles génomique, visualisations et analyse d’expression génique et une analyse d’un microbiome.

Une liste des packages nécessaires sera transmise directement aux participants.