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Online Workshop: BIOF 043 | For True BeginRs – Hands-on R Training

September 15, 2020 @ 9:00 AM September 17, 2020 @ 5:00 PM

R is a free, cross-platform – Windows, Mac, and Linux – programming language, designed specifically to facilitate data management, analysis, and visualization. Boasting vibrant development and support communities, R has become an indispensable tool for bioinformaticians, statisticians, and data scientists. Created with true beginRs in mind, this training will teach participants the fundamental, transferable skills needed to unleash R’s full potential for producing publication-worthy analyses and visualizations.

– Our goal is simple: to flatten the (learning) curve. Using transparent, illustrative examples and exercises, participants will get hands-on walkthroughs on:
– Interfacing with R using RStudio;
– Using RStudio’s built-in help function – ? – as well as resources for troubleshooting, including rdocumentation.org, cheat sheets, vignettes, YouTube channels, and stackexchange.com;
– Creating project files;
– Working with the RStudio command line;
– Identifying and changing the current working file directory;
– Variables – local vs. global – naming conventions, and assignment operators;
– Writing their first R script and how to properly document their code via commenting;
– Using the ‘$’ accessor function;
– Basic “for” loops;
– The most common data types, including character strings, numerical, integers, and logicals;
– How to access data entries using [] and [[ ]];
– The most common data structure types, including vectors, lists, factors, data frames, and tibbles;
– Package libraries and how to install them;
– Loading data into R and basic troubleshooting when importing data;
– Data management, manipulation, subsetting, piping, and exploration using dplyr;
– The concept of “tidy” data, the “tidyverse”, and the tools for transforming untidy data into tidy data;
– Creating and exporting highly customizable, publication-quality data visualizations with ggplot2;
– Using R to perform statistical analyses, including simple linear regression, χ2 contingency table analysis, two-sample t-tests, and analysis of variance;
– Advanced graphics packages and dynamic, interactive plots (if time permits);
– Using Github for script version control (if time permits);
– Basic machine learning applications using caret (if time permits).

We will work in RStudio, an integrated development environment (IDE) built specifically for R. A copy of all the scripts used in class to import and tidy data, create visualizations, and perform analyses will be provided to each participant at the end of the training. Participants will also have access to a free online cookbook style manual for all exercises, which can be saved in PDF format for offline use

Who Should Attend:
Those new to programming and data science techniques;
Anyone interested in learning the most fundamental, transferable skills in R;
Beginners looking for a free alternative to proprietary software applications like STATA, SAS, and MATLAB


September 15 @ 9:00 AM
September 17 @ 5:00 PM
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FAES@National Instutes of Health in Bethesda

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