library(tidyverse)
+library(readxl)Content
-Core 1
-Note no R coding (too early for 70M)
+Overview You are either an integrated masters student doing 88H Group Project or a MSc Bioinformatics student doing 70M
+Week 1 Core 1 Organising Reproducible Data Analyses
+Note no R coding (too early for MSc BIN 70M who share the core and omics teaching)
+Before - Optional revision: What they forgot to teach you about computers: operating systems, file systems, file types, working directories and paths
+-
+
- Why reproducibility (BIO00058M-Data-science-2020/slides/03_repro_and_intro_to_rmarkdown) +
Workshop
- Project organisation: folders, files
- Project oriented workflow -
- Readme
- Naming things -
- Keeping notes -
- Data management, google drive: https://www.york.ac.uk/it-services/services/drive/#tab-6 -
- file formats -
- Introduction to data in general. Similarities and differences +
- File formats +
- Data management
+
-
+
- google drive: https://www.york.ac.uk/it-services/services/drive/#tab-6 +
- documenting +
- organisation within files +
+ - Data files. Similarities and differences
- Sequences data
- Image data
- Structure data.
+ - Keeping notes +
- Readme +
- Reference managers: Zotero
After
Core 2
-rgetgretger
+Week 2 Core 2 NEEDS A TITLE
+Before Possibly: Code formatting and style, 😎 Cool code Tips, Code ‘algorithmically.’, Writing functions (R and python??) (BIO00058M-Data-science-2020/slides/03_repro_and_intro_to_rmarkdown)
+Workshop
+After
Core 3: Quarto
-fgzzdfghdfhg
+Week 6 Core 3 Reproducible Reporting
+Before (BIO00058M-Data-science-2020/slides/03_repro_and_intro_to_rmarkdown and BIO00058M-Data-science-2020/slides/04_advanced_rmarkdown.html) Literate programming What is quarto markdown basics: text, code chunks, headings yaml automatic numbering of figures and tables cross references special characters citations
+Workshop
+practice doing the above with your project and data
+After
-
@@ -209,25 +209,25 @@
-
-
-
- 📖 Read ddd +
- 📖 Read What they forgot to teach you about computers
-
-
diff --git a/core/week-1/study_after_workshop.html b/core/week-1/study_after_workshop.html
index e538f7a..0f461a9 100644
--- a/core/week-1/study_after_workshop.html
+++ b/core/week-1/study_after_workshop.html
@@ -207,25 +207,25 @@
- Introduction
- Getting started
- Exercises @@ -282,7 +281,7 @@
- don’t worry about making mistakes -
- don’t let what you can not do interfere with what you can do -
- discussing code with your neighbours will help -
- look things up in the independent study material -
- look things up in your own code from earlier workshops -
- there are no stupid questions -
-
@@ -243,25 +243,25 @@
-
diff --git a/core/week-1/study_before_workshop.html b/core/week-1/study_before_workshop.html
index b913a5b..88377d4 100644
--- a/core/week-1/study_before_workshop.html
+++ b/core/week-1/study_before_workshop.html
@@ -173,25 +173,25 @@
-
@@ -209,25 +209,25 @@
-
diff --git a/core/week-1/workshop.html b/core/week-1/workshop.html
index 2837838..c304172 100644
--- a/core/week-1/workshop.html
+++ b/core/week-1/workshop.html
@@ -192,25 +192,25 @@
-
@@ -228,25 +228,25 @@
-
@@ -265,7 +265,6 @@
On this page
On this page
@@ -301,19 +300,7 @@Workshop
-xxx
+Organising Reproducible Data Analyses
Workshop
Introduction
Session overview
-In this workshop you will learn to summarise and plot datasets with more than one variable and how to write figures to files. You will also get more practice with working directories, importing data, formatting figures and the pipe.
-- Philosophy
-Workshops are not a test. It is expected that you often don’t know how to start, make a lot of mistakes and need help. It is expected that you are familiar with independent study content before the workshop. However, you need not remember or understand every detail as the workshop should build and consolidate your understanding. Tips
--
-
In this workshop you will
-These four symbols are used at the beginning of each instruction so you know where to carry out the instruction.
-
-
Something you need to do on your computer. It may be opening programs or documents or locating a file.
-
Something you should do in RStudio. It will often be typing a command or using the menus but might also be creating folders, locating or moving files.
-
Something you should do in your browser on the internet. It may be searching for information, going to the VLE or downloading a file.
+
A question for you to think about and answer. Record your answers in your script for future reference.
-
@@ -245,7 +245,7 @@
Overview
-Core 1
+Core 1: Organising Data Analyses
Instructions
Getting started
-Start RStudio make an RStudio project for this workshop.
-Make a new folder called data-raw.
Make a new script then save it to carry out the rest of the work.
-Add code to load the tidyverse package (Wickham et al. 2019)
Exercises
+🎬 - Project organisation: folders, files - Project oriented workflow - Naming things - File formats - Data management - google drive: https://www.york.ac.uk/it-services/services/drive/#tab-6 - documenting - organisation within files - Data files. Similarities and differences - Sequences data - Image data - Structure data. - Keeping notes - Readme - Reference managers: Zotero
You’re finished!
The Code file
R Core Team. 2023. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
-
-Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the Tidyverse” 4: 1686. https://doi.org/10.21105/joss.01686.
-
Xie, Yihui. 2022. “Knitr: A General-Purpose Package for Dynamic Report Generation in r.” https://yihui.org/knitr/.
diff --git a/core/week-2/overview.html b/core/week-2/overview.html
new file mode 100644
index 0000000..2bc0bc2
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