Web Page
Bioinformatics
Material from this lesson was adapted from Chapter 3 of R for Data Science and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Doyle and Stefano Mangiola.
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from Intro to R and RStudio for Genomics provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Doyle and Read More...
Web Page
Bioinformatics
Material from this lesson was adapted from Chapter 3 of R for Data Science and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Doyle and Stefano Mangiola.
Web Page
Bioinformatics
Material from this lesson was adapted from Chapter 3 of R for Data Science and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Doyle and Stefano Mangiola.
Web Page
Bioinformatics
Material from this lesson was adapted from Chapter 3 of R for Data Science and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Doyle and Stefano Mangiola.
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Read More...
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Read More...
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Read More...
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Read More...
Web Page
Bioinformatics
Material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org and from a 2021 workshop entitled Introduction to Tidy Transciptomics by Maria Read More...
Web Page
Bioinformatics
There are data sets available in R to practice with or showcase different packages. For today's lesson and the remainder of this course, we will use data from the Bioconductor package airway to showcase Read More...
Web Page
Bioinformatics
There are data sets available in R to practice with or showcase different packages. For today's lesson and the remainder of this course, we will use data from the Bioconductor package airway to showcase Read More...
Rockville, MD
Collaborative
We are a bioinformatics team within the Center for Biomedical Informatics and Information Technology’s (CBIIT’s) Cancer Informatics Branch (CIB)—soon to be referred to as the Informatics and Data Science (IDS) Program. Headed Read More...
Web Page
Bioinformatics
Learning Objectives Learn about data structures including factors, lists, data frames, and matrices. Load, explore, and access data in a tabular format (data frames) Learn to write out (export) data from the R environment Data Read More...
Web Page
Bioinformatics
Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...
Web Page
Bioinformatics
In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...
Web Page
Bioinformatics
In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...
Web Page
Bioinformatics
This lesson will introduce data wrangling with R. Attendees will learn to filter data using base R and tidyverse (dplyr) functionality. Learning Objectives Understand the concept of tidy data. Become familiar with the tidyverse packages. Read More...
Web Page
Bioinformatics
Introduction to ggplot2 Objectives Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective figures. Data Visualization in the tidyverse Read More...
Web Page
Bioinformatics
Introduction to ggplot2 Objectives Learn how to import spreadsheet data. Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective Read More...
Web Page
Bioinformatics
Data frames Objectives To be able to load, explore, and access data in a tabular format. To this end, students should understand the following: 1. how to import and export data 2. how to create, summarize, and Read More...
Web Page
Bioinformatics
Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...
Web Page
Bioinformatics
Introduction to Data Wrangling with the Tidyverse Objectives Wrangle data using tidyverse functionality (i.e., dplyr ). To this end, you should understand: 1. how to use common dplyr functions (e.g., select() , group_by() , arrange() , mutate() , Read More...