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TOPIC: R
- Access to R, lessons will be taught through RStudio Cloud
- (Optional) Command line experience
- Lesson 1: Introduction to R & Acces to Rstudio Cloud
- Lesson 2: Dealing with Data Frames
- Lesson 3: Introduction to Tidyverse
- Lesson 4: Dealing with NA
- Lesson 5: Introduction to Plotting
- Lesson 6: Plotting & Data Wrangling Part II
- Lesson 7: Correlations and linear models
- Lesson 8: Ordination - Linked with Lesson 5 in Topic Amplicon
Date posted: 06 April 2020
Author(s): Dr. Sarah Hu, Dr. Liz Suter, Dr. Alexis Marshall
Instructor(s): Dr. Sarah Hu, Dr. Liz Suter, Dr. Alexis Marshall
- Understand RStudio working environment
- Basic syntax in R
- Assigning a variable
Date posted: 08 April 2020
Author(s): Dr. Sarah Hu, Dr. Liz Suter, Dr. Alexis Marshall
Instructor(s): Dr. Sarah Hu, Dr. Liz Suter, Dr. Alexis Marshall
Date posted: 11 April 2020
Author(s): Dr. Ella Sieradzki
Instructor(s): Dr. Ella Sieradzki
- Basic data table manipulation
- Import test data into R from .csv format
- Applying basic functions to a data table
Date posted: 20 April 2020
Author(s): Dr. Ella Sieradzki
Instructor(s): Dr. Ella Sieradzki
Date posted: 22 April 2020
Author(s): Dr. Sarah Hu
Instructor(s): Dr. Sarah Hu
- Overview of data frames, matrices, and tibbles
- Showing how to work with data tables in base R vs. Tidyverse
Date posted: 22 April 2020
Author(s): Dr. Sarah Hu
Instructor(s): Dr. Sarah Hu
Date posted: 6 May 2020
Author(s): Dr. Philip Leftwich
Instructor(s): Dr. Philip Leftwich
- Using RMarkdown format to plan chunks of code
- Tutorial on how R handles empty (NA) data cells
Date posted: 9 May 2020
Author(s): Dr. Ella Sieradzki
Instructor(s): Dr. Ella Sieradzki
- Scatter plots in base R and ggplot2
Date posted: 14 May 2020
Author(s): Dr. Sarah Hu
Instructor(s): Dr. Sarah Hu
- Bar plots and box plots with ggplot2
- Plot annotations (e.g., colors, axis labels, etc.)
- Tidyverse data wrangling review
- Long-format data frame
- Making a taxonomy bar plot
Date posted: 26 May 2020
Author(s): Dr. Jacob Cram
Instructor(s): Dr. Jacob Cram
Date posted: 6 June 2020
Author(s): Dr. Jacob Cram
Instructor(s): Dr. Jacob Cram
Date posted: 26 June 2020
Author(s): Dr. Liz Suter
Instructor(s): Dr. Liz Suter
- Amplicons crossover tutorial, see Topic Amplicons Lesson 5 for more
- Using the output from Qiime2 analysis in Topic Amplicons Lesson 4
- Import ASV table into phyloseq
- Explore functionality of phyloseq: making tree, re-rooting tree, bar plot of taxa
- Ordinations with phyloseq: PCoA, weighted UniFrac PCoA, NMDS
Primary tools/programs used:
Date posted: 7 July 2020
Author(s): Dr. Sarah Hu
Instructor(s): Dr. Sarah Hu
Content | Video presentation - Part 1 | Video presentation - Part 2
- R cheatsheets for base R
- Cheatsheet for Tidyverse: ggplot2 and data wrangling
- Cheatsheet for stringr
- Riffomonas from Pat Schloss's group
- R for data science
- From Happy Belly Bioinformatics:
- List of keyboard shortcuts, Windows and Mac
- Execute command in R: (Mac) COMMAND+ENTER and (PC) CONTROL+ENTER
- Comment (
#) or uncomment whole line: (Mac) COMMAND+SHIFT+C and (PC) CONTROL+SHIFT+C - Insert
->operator: (Mac) OPTION+- and (PC) ALT+-
- When you do cbind does it make it a dataframe and if not what is the difference between dataframes and cbinding?
Answer: cbind() makes a matrix, while data.frame() makes a dataframe, otherwise they behave very similarly. To add, if you cbind() numeric and character type columns, it will make everything a character (because matrices require all contents are the same data type.- Compare data frames and matrices: Data frames and matrices are similar, but have some key differences. Matrices are basically a grid of things, those could be numbers or character strings. Data frames are technically lists, so each column can be a column of different data "types". Meaning, one column of a dataframe could be words (Factors) and other numbers.
- For index locations in lists or matrices, the first item is index 1, is this correct? (vs. python with 0 indexing) Answer: yes!
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