Natalie Elphick
Bioinformatician I
Min-Gyoung Shin
-Bioinformatician III
[1] NAWhich of these is not the correct data type for the value?
10:00
x == y # Equal to
-x != y # Not equal to
-x < y # Less than
-x > y # Greater than
-x <= y # Less than or equal to
-x >= y # Greater than or equal to
-
-x %in% y # Is x in this vector y?What is the output of the following code?
- -What is the output of the following code?
+ +What is the output of the following code?
- +dog_breeds <- c("Labrador Retriever", "Akita", "Bulldog")
-
-if ("Akita" %in% dog_breeds) {
-
- print("dog_breeds already contains Akita")
-
-} else {
-
- dog_breeds <- c("Akita", dog_breeds)
-
-}dog_breeds <- c("Labrador Retriever", "Akita", "Bulldog")
+
+if ("Akita" %in% dog_breeds) {
+
+ print("dog_breeds already contains Akita")
+
+} else {
+
+ dog_breeds <- c("Akita", dog_breeds)
+
+}[1] "dog_breeds already contains Akita"[1] "Already contains this dog"add_dog(dog_to_add = "German Shepard",
+
+[1] "Already contains this dog"
+
[1] "German Shepard" "Labrador Retriever" "Akita"
[4] "Bulldog"
Poll 6
What does this function do?
-
+
- Returns the absolute value of x
- Returns x
@@ -3070,7 +3076,7 @@ specified with the return function:
- Packages are collections of functions that are specialized to a
specific task (plotting, data manipulation etc.)
-
+
- The tidyverse is a collection of commonly used data analysis
packages
@@ -3110,15 +3116,15 @@ can continue to improve these workshops
Upcoming Workshops
-Intermediate
-RNA-Seq Analysis Using R
-September 10, 2024 9am-12pm PDT
-Introduction
-to Statistics, Experimental Design, and Hypothesis Testing
-September 10 - September 12, 2024 1-3pm PDT
-Single
-Cell RNA-Seq Data Analysis
-September 16-September 17, 2024 9am-4pm PDT
+Introduction
+to scATAC-seq Data Analysis
+November 14 - November 15, 2024 1:00-4:00pm PST
+Introduction
+to Linear Mixed Effects Models
+November 18-November 19, 2024 1:00-3:00pm PST
+scATAC-seq
+and scRNA-seq Data Integration
+November 22, 2024 1:00-4:00pm PST
- Check this
link at for the full schedule
diff --git a/docs/Intro_to_R_data_analysis_part_2.html b/docs/Intro_to_R_data_analysis_part_2.html
index ef40e72..77e4a05 100644
--- a/docs/Intro_to_R_data_analysis_part_2.html
+++ b/docs/Intro_to_R_data_analysis_part_2.html
@@ -2809,10 +2809,8 @@ border: 0;
Introductions
Natalie Elphick
Bioinformatician I
-Michela Traglia
-Senior Statistician
-Ayushi Agrawal
-Bioinformatician III
+Reuben Thomas
+Associate Core Director
@@ -3048,7 +3046,7 @@ modified by adding layers
10 min break
-
+
10:00
@@ -4624,8 +4622,23 @@ reach out to the authors using their preferred method
Additional Resources
-
-R
+
+Coding Templates
+Code templates can be used to avoid typing the same code over and
+over again.
+
+- These are templates that we are using to automate things like plot
+appearance and documentation:
+
+
+
+
+R Resources
-
-
-Statistics
-
-- Data Analysis in
-R : This book has more statistics details than R for Data
-Science
-- Generalized
-Linear Models
-
-- Random
-Effects
-
-
-
-RNA-seq Analysis
-
-- RNA-seqlopedia :
-Everything you need to know about RNA-seq experiments
-- RNA-seq
-Expression Units : Blog post on understanding common units
-- Introduction
-to Single-Cell Analysis with Bioconductor : Covers the basics of
-scRNA-seq analysis in R
-
-
-
-Dimensional Reduction
-
-- Tutorial
-on PCA : PCA explained with R code examples
-- Understanding
-UMAP : Short explanation with great visualizations, mainly useful
-for scRNA-seq analysis
-
@@ -4686,15 +4664,15 @@ can continue to improve these workshops
Upcoming Workshops
-Intermediate
-RNA-Seq Analysis Using R
-September 10, 2024 9am-12pm PDT
-Introduction
-to Statistics, Experimental Design, and Hypothesis Testing
-September 10 - September 12, 2024 1-3pm PDT
-Single
-Cell RNA-Seq Data Analysis
-September 16-September 17, 2024 9am-4pm PDT
+Introduction
+to scATAC-seq Data Analysis
+November 14 - November 15, 2024 1:00-4:00pm PST
+Introduction
+to Linear Mixed Effects Models
+November 18-November 19, 2024 1:00-3:00pm PST
+scATAC-seq
+and scRNA-seq Data Integration
+November 22, 2024 1:00-4:00pm PST
- Check this
link at for the full schedule
diff --git a/intro-r-data-analysis/Intro_to_R_data_analysis_part_1.Rmd b/intro-r-data-analysis/Intro_to_R_data_analysis_part_1.Rmd
index 5072fe8..cb8f4f6 100644
--- a/intro-r-data-analysis/Intro_to_R_data_analysis_part_1.Rmd
+++ b/intro-r-data-analysis/Intro_to_R_data_analysis_part_1.Rmd
@@ -2,7 +2,7 @@
title: "Introduction to R Data Analysis"
subtitle: "Part 1"
author: "Natalie Elphick"
-date: "August 26th, 2024"
+date: "November 11th, 2024"
knit: (function(input, ...) {
rmarkdown::render(
input,
@@ -29,8 +29,7 @@ knitr::opts_chunk$set(comment = "")
**Natalie Elphick**
Bioinformatician I
-**Min-Gyoung Shin**
-Bioinformatician III
+
## Poll 1
@@ -246,19 +245,27 @@ DogBreeds <- c("Labrador Retriever", "Akita", "Bulldog")
- Decimal numbers
- Logical
- Boolean (TRUE, FALSE)
- - NA (missing data)
- Character
- Letters and strings of letters
- "A", "Labrador Retriever"
+## Missing Values
+- R has a special data type - NA which represents missing data
+- NAs can take the place of any type but by default are logical
+```{r}
+NA + 1
+```
+
+
## Poll 3
**Which of these is not the correct data type for the value?**
-1. 1.5 - Numeric
-2. "1" - Character
-3. NA - Logical
-4. 1 - Integer
+1. "1.5" - Numeric
+2. "A" - Character
+3. 1L - Integer
+4. TRUE - Boolean
+
## Data Structures
@@ -320,17 +327,7 @@ x >= y # Greater than or equal to
x %in% y # Is x in this vector y?
```
-## Poll 4
-**What is the output of the following code?**
-
-```{r, eval = FALSE}
-4 %in% c(1, 2, 3, 4)
-```
-
-1. TRUE
-2. FALSE
-3. NA
## Logical Operators
@@ -344,6 +341,18 @@ x | y # x or y
x & y # x and y
```
+## Poll 4
+
+**What is the output of the following code?**
+
+```{r, eval = FALSE}
+2 + 2 == 4 & 8 + 10 < 20
+```
+
+1. TRUE
+2. FALSE
+3. NA
+
## Poll 5
**What is the output of the following code?**
@@ -351,7 +360,7 @@ x & y # x and y
x <- TRUE
y <- FALSE
-x & !y
+y | (y | x)
```
1. TRUE
@@ -470,16 +479,17 @@ packages
## Upcoming Workshops
-[Intermediate RNA-Seq Analysis Using R](https://gladstone.org/events/intermediate-rna-seq-analysis-using-r-5)
-September 10, 2024 9am-12pm PDT
+[Introduction to scATAC-seq Data Analysis](https://gladstone.org/events/introduction-scatac-seq-data-analysis)
+November 14 - November 15, 2024 1:00-4:00pm PST
-[Introduction to Statistics, Experimental Design, and Hypothesis Testing](https://gladstone.org/events/introduction-statistics-experimental-design-and-hypothesis-testing-1)
-September 10 - September 12, 2024 1-3pm PDT
+[Introduction to Linear Mixed Effects Models](https://gladstone.org/events/introduction-linear-mixed-effects-models-0)
+November 18-November 19, 2024 1:00-3:00pm PST
-[Single Cell RNA-Seq Data Analysis](https://gladstone.org/events/single-cell-rna-seq-data-analysis-0)
-September 16-September 17, 2024 9am-4pm PDT
+[scATAC-seq and scRNA-seq Data Integration](https://gladstone.org/events/scatac-seq-and-scrna-seq-data-integration)
+November 22, 2024 1:00-4:00pm PST
- Check [this link](https://gladstone.org/events?series=data-science-training-program) at for the full schedule
+
diff --git a/intro-r-data-analysis/Intro_to_R_data_analysis_part_2.Rmd b/intro-r-data-analysis/Intro_to_R_data_analysis_part_2.Rmd
index 8c963c9..014d3f5 100644
--- a/intro-r-data-analysis/Intro_to_R_data_analysis_part_2.Rmd
+++ b/intro-r-data-analysis/Intro_to_R_data_analysis_part_2.Rmd
@@ -31,11 +31,8 @@ knitr::opts_chunk$set(comment = "")
**Natalie Elphick**
Bioinformatician I
-**Michela Traglia**
-Senior Statistician
-
-**Ayushi Agrawal**
-Bioinformatician III
+**Reuben Thomas**
+Associate Core Director
# Schedule
@@ -281,30 +278,23 @@ For any bioinformatics specific questions feel free to reach out to the Gladston
# Additional Resources
+## Coding Templates
-## R
+Code templates can be used to avoid typing the same code over and over again.
+
+- These are templates that we are using to automate things like plot appearance and documentation:
+ - [.Rmd Template](https://www.dropbox.com/scl/fi/a9cnyqdajgabbfcxbmm6y/RMD_template.Rmd?rlkey=yntfpo6aptw9b4pgjyzpe5ubi&dl=1)
+ - [.R Script Template](https://www.dropbox.com/scl/fi/cy43b8b1x3nzn17esnmmt/Rscript_template.R?rlkey=zn7b0g8nn0s9213blh70fjjsx&dl=1)
+
+
+
+## R Resources
- [R for Data Science](https://r4ds.hadley.nz/)
- [Top 10 R Errors and How to Fix them](https://statsandr.com/blog/top-10-errors-in-r/)
- [R Markdown: The Definitive Guide](https://bookdown.org/yihui/rmarkdown/how-to-read-this-book.html)
- [ggplot2: elegant graphics for data analysis](https://ggplot2-book.org/)
- [Advanced R](https://adv-r.hadley.nz/)
-## Statistics
-
-- [Data Analysis in R](https://bookdown.org/steve_midway/DAR) : This book has more statistics details than *R for Data Science*
-- [Generalized Linear Models](https://bookdown.org/steve_midway/DAR/glms-generalized-linear-models.html)\
-- [Random Effects](https://bookdown.org/steve_midway/DAR/random-effects.html)
-
-## RNA-seq Analysis
-
-- [RNA-seqlopedia](https://rnaseq.uoregon.edu/) : Everything you need to know about RNA-seq experiments
-- [RNA-seq Expression Units](https://luisvalesilva.com/datasimple/rna-seq_units.html) : Blog post on understanding common units
-- [Introduction to Single-Cell Analysis with Bioconductor](https://bioconductor.org/books/3.17/OSCA.intro/index.html) : Covers the basics of scRNA-seq analysis in R
-
-## Dimensional Reduction
-
-- [Tutorial on PCA](https://uw.pressbooks.pub/appliedmultivariatestatistics/chapter/pca/) : PCA explained with R code examples
-- [Understanding UMAP](https://pair-code.github.io/understanding-umap/) : Short explanation with great visualizations, mainly useful for scRNA-seq analysis
@@ -315,14 +305,14 @@ For any bioinformatics specific questions feel free to reach out to the Gladston
## Upcoming Workshops
-[Intermediate RNA-Seq Analysis Using R](https://gladstone.org/events/intermediate-rna-seq-analysis-using-r-5)
-September 10, 2024 9am-12pm PDT
+[Introduction to scATAC-seq Data Analysis](https://gladstone.org/events/introduction-scatac-seq-data-analysis)
+November 14 - November 15, 2024 1:00-4:00pm PST
-[Introduction to Statistics, Experimental Design, and Hypothesis Testing](https://gladstone.org/events/introduction-statistics-experimental-design-and-hypothesis-testing-1)
-September 10 - September 12, 2024 1-3pm PDT
+[Introduction to Linear Mixed Effects Models](https://gladstone.org/events/introduction-linear-mixed-effects-models-0)
+November 18-November 19, 2024 1:00-3:00pm PST
-[Single Cell RNA-Seq Data Analysis](https://gladstone.org/events/single-cell-rna-seq-data-analysis-0)
-September 16-September 17, 2024 9am-4pm PDT
+[scATAC-seq and scRNA-seq Data Integration](https://gladstone.org/events/scatac-seq-and-scrna-seq-data-integration)
+November 22, 2024 1:00-4:00pm PST
- Check [this link](https://gladstone.org/events?series=data-science-training-program) at for the full schedule
diff --git a/intro-r-data-analysis/lesson_0/lesson_0.Rmd b/intro-r-data-analysis/lesson_0/lesson_0.Rmd
index 8e2b9cf..e9822e4 100644
--- a/intro-r-data-analysis/lesson_0/lesson_0.Rmd
+++ b/intro-r-data-analysis/lesson_0/lesson_0.Rmd
@@ -23,7 +23,7 @@ learnr::tutorial_options(exercise.timelimit = 10)
This guide will help you get set up for Intro to R Data Analysis. There are just a few steps to make sure you'll have the necessary software installed and ready to go on day 1. **Please ensure that you've completed each step by running the validation test prior to the start of the workshop**.
-This guide will walk you through how to install R, RStudio, and some additional tools that we’ll be using in the course. By rough analogy to a car, R is like the car’s engine and RStudio is like the dashboard. More precisely, R is a programming language and Rstudio is an ‘integrated development environment’ (IDE), which is basically a nice software interface for interacting with R. For our purposes, you will only ever interact directly with RStudio, but it needs to have R installed to work (like a car needing its engine).
+This guide will help you set up R, RStudio, and a few extra tools we'll use in this course. You can think of R as the engine that powers everything, while RStudio is like the dashboard that makes it easy to control. R is a programming language, and RStudio is a tool that helps you work with it. Even though you'll mainly use RStudio, it needs R to be installed to work, just like a car needs an engine to run.
Please complete the following steps (must be done in this order). If you already have R and Rstudio installed you can skip ahead. Make sure you complete step 5 though!
@@ -83,4 +83,4 @@ You should see a plot that looks like this appear:
-If you see an error that says “R version is too old” that means you need to update your R version. The update process is the same as the installation process. It will update your R installation. If you see an error that says “There is no package called ggplot2” that means you need to install the tidyverse package (see above).
+If you see an error that says “R version is too old” that means you need to update your R version. The update process is the same as the installation process. It will update your R installation. If you see an error that says “There is no package called ggplot2” that means you need to install the tidyverse package (see the *Install Required Packages* section).