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R User Group

The R User Group meets weekly to discuss programming, data analysis, and troubleshooting in R. Bring your lunch, code, questions, and thoughts! R coders of all levels of expertise are welcome. Contact the Coop (coophelp at fredhutch.org) for more information. Additionally, check out the #r-user-comm channel on the Coop Communities Slack and our other training and community resources at Training, Community and Finding Help . Note: If you do not have a laptop available to you we still want you to come!! You can email code privately ahead of each event to Amy Paguirigan (apaguiri at fredhutch.org). Current meeting schedules and locations are available on the Google calendar.

Please see this issue to add topics for discussion at these meetings!

The freddie repository is a collaborative, community-developed package of useful R functions being developed by the R community at Fred Hutch. The goal of freddie is to collect helper functions and tools that Fred Hutch R community folk create.

Here are some more useful links:

  • R is a language and environment for statistical computing and graphics
  • CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for 
  • RStudio is an open source, enterprise software for data science
  • Tidyverse is a collection of R packages for data science. git repo
  • dplyr - Data Wrangling and Transformation - A fast, consistent tool for working with data frame like objects, both in memory and out of memory.
  • tidyr - Data Wrangling and Transformation - An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines.
  • stringr - Data Wrangling and Transformation - Simple, Consistent Wrappers for Common String Operations
  • forcats - Data Wrangling and Transformation - Tools for Working with Categorical Variables (Factors)
  • tibble - Data Import and Management - Provides a 'tbl_df' class that offers better checking and printing capabilities than traditional data frames.
  • readr - Data Import and Management - The goal of 'readr' is to provide a fast and friendly way to read rectangular data (like 'csv', 'tsv', and 'fwf'). It is designed to flexibly parse many types of data found in the wild, while still cleanly failing when data unexpectedly changes.
  • purrr - Functional Programming - A complete and consistent functional programming toolkit for R.
  • ggplot2 - Data Visualization and Exploration - Create Elegant Data Visualisations Using the Grammar of Graphics
  • DataExplorer - Data Visualization and Exploration - Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights.
  • esquisse - Data Visualization and Exploration - A 'shiny' gadget to create 'ggplot2' charts interactively with drag-and-drop to map your variables.
  • parsnip - Machine Learning - A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. R, spark, stan, etc).
  • Ranger - Machine Learning - A Fast Implementation of Random Forests
  • Reticulate - Miscellaneous Package - Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types.
  • InstallR - Miscellaneous Package - R is great for installing software. Through the 'installr' package you can automate the updating of R (on Windows, using updateR()) and install new software.
  • GitHubInstall - Miscellaneous Package - Provides an helpful way to install packages hosted on GitHub.
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