Canadian Bioinformatics Workshops is offering two workshops on using R: a one-day Introduction to R workshop (June 6, 2016) and a two-day Exploratory Analysis of Biological Data using R workshop (June 7 - June 8, 2016) in Toronto, Ontario.
Introduction to R introduces the essential ideas and tools of R. We will work in a problem-based scenario in which we analyze a real world challenge in data handling. As we break down the problem into structured parts, we explore R syntax, functions and packages – and in general explore best practices for scientific computational work.
Exploratory Analysis of Biological Data (EDA) using R introduces the essential tools and strategies that are available for EDA through the free statistical workbench R. Working from hands-on scripts that cover key aspects of EDA, participants learn to use R and its analysis tools, read and modify code, and explore protocols that can be adapted for their own research tasks. Steps covered in this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more. Writing your own R functions and analysis scripts will be introduced at the beginning of the workshop and skills will be gradually built on over the course of the lectures. Plotting and visualization is a key element of EDA and we will gradually build skills–from the elementary built-in routines via their (sometimes bewildering) array of parameters to sophisticated, publication-ready presentations.
For more information and to apply, please visit the workshop website.
Introduction to R introduces the essential ideas and tools of R. We will work in a problem-based scenario in which we analyze a real world challenge in data handling. As we break down the problem into structured parts, we explore R syntax, functions and packages – and in general explore best practices for scientific computational work.
Exploratory Analysis of Biological Data (EDA) using R introduces the essential tools and strategies that are available for EDA through the free statistical workbench R. Working from hands-on scripts that cover key aspects of EDA, participants learn to use R and its analysis tools, read and modify code, and explore protocols that can be adapted for their own research tasks. Steps covered in this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more. Writing your own R functions and analysis scripts will be introduced at the beginning of the workshop and skills will be gradually built on over the course of the lectures. Plotting and visualization is a key element of EDA and we will gradually build skills–from the elementary built-in routines via their (sometimes bewildering) array of parameters to sophisticated, publication-ready presentations.
For more information and to apply, please visit the workshop website.