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Feature/core updater 2024
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3mmaRand authored Oct 20, 2024
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16 changes: 13 additions & 3 deletions core/week-2/overview.qmd
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---

This week you will revise some essential concepts for scientific computing: file system organisation, file types, working directories and paths. The workshop will cover a rationale for working reproducibly, project oriented workflow, naming things and documenting your work.
This week you will revise some essential concepts for scientific computing:
file system organisation, file types, working directories and paths. You will
also ensure you know how to use the virtual desktop service (VDS) to access
the software you need for your work.
The workshop will cover a rationale for working reproducibly,
project oriented workflow, naming things and documenting your work.


### Learning objectives

The successful student will be able to:

- explain the organisation of files and directories in a file systems including root, home and working directories
- explain the organisation of files and directories in a file
systems including root, home and working directories
- explain absolute and relative file paths
- explain why working reproducibly is important
- know how to use a project-oriented workflow to organise work
- be able to give files human- and machine-readable names
- write cool 😎 code not 😩 ugly code
- explain the value of code which expresses the structure of the problem/solution.
- explain the value of code which expresses the structure of the
problem/solution.
- use some useful shortcuts to help write cool 😎 code
- ensure they can use the VDS to access files and software
required for the work

### Instructions

1. [Prepare](study_before_workshop.qmd)

i. πŸ“– Read Understanding file systems
ii. πŸ“– Read Workflow in RStudio
iii. πŸ–₯️Set up the VDS and know how to use it.

2. [Workshop](workshop.qmd)

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---

These are suggestions
Before starting work on your strand specific data analysis. Ensure you have
EITHER:

- 🎬 Set up the [Virtual Desktop Service](https://www.york.ac.uk/it-services/tools/vds/)
and been able to use it

- Want github co-pilot?

🎬 Create a [GitHub account](https://github.com/)
OR

🎬 Apply for [student
benefits](https://education.github.com/discount_requests/application)
- 🎬 [Updated R](https://www.r-project.org/)

- Update R and RStudio

🎬 [Update R](https://www.r-project.org/)

🎬 [Update RStudio](https://posit.co/download/rstudio-desktop/).
- 🎬 [Updated RStudio](https://posit.co/download/rstudio-desktop/).

- Install package building tools

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🎬 Mac install [Xcode from Mac App
Store](https://apps.apple.com/ca/app/xcode/id497799835?mt=12)

- Update packages:
- 🎬 Installed packages: **`devtools`**, **`tidyverse`**, **`BiocManager`**,
**`readxl`**



You might want to consider getting a GitHub account and applying for
student benefits so that you can use GitHub co-pilot. GitHub copilot is an
β€œAI pair programmer that offers autocomplete-style suggestions as you code”.
GitHub Copilot is available as an opt-in integration with RStudio.

- Read more about [GitHub Copilot integration
with RStudio](https://docs.posit.co/ide/user/ide/guide/tools/copilot.html)

🎬 devtools, tidyverse, BiocManager, readxl
- 🎬 Create a [GitHub account](https://github.com/)

- 🎬 Apply for [student
benefits](https://education.github.com/discount_requests/application).
You will need to upload an image of your student id, use your institutional
email address and you will be required to use two factor authentication.
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1. πŸ“– Read [Understanding file systems](https://3mmarand.github.io/comp4biosci/file_systems.html). This is an approximately 15 - 20 minute read revising file types and file systems. It covers concepts of working directories and paths. We learned these ideas in stage 1 and you may feel completely confident with them but many students will benefit from a refresher. For BIO00070M students, this is part of the work you will also be asked to complete for BIO00052M Data Analysis in R.

2. πŸ“– Read [Workflow in RStudio](https://3mmarand.github.io/comp4biosci/workflow_rstudio.html). You may find it helpful to remind yourself about RStudio Projects. In previous years, you have submitted an "RStudio Project" as part of your BABS work. In this module, you will submit "Supporting Information" for your Project Report. The Supporting Information is a documented and organised collection of all the digital parts of your research project. This includes data (or instructions for accessing data), code and/or non-coded processing, instructions for use, computational requirements and outputs. The Supporting Information could be a single RStudio Project (like you have done previously but with better documentation) or a folder that includes an RStudio Project and other material/scripts.
2. πŸ“– Read [Workflow in RStudio](https://3mmarand.github.io/comp4biosci/workflow_rstudio.html). You may find it helpful to remind yourself about RStudio Projects. In previous years, you have submitted an "RStudio Project" as part of your BABS work. In this module, you will submit "Supporting Information" for your Project Report. The Supporting Information is a documented and organised collection of all the digital parts of your research project. This includes data (or instructions for accessing data), code and/or non-coded processing, instructions for use, computational requirements and outputs. The Supporting Information could be a single RStudio Project (like you have done previously but with better documentation) or a folder that includes an RStudio Project and other material/scripts.

3.πŸ’» Set up the Virtual Desktop. I very strongly recommend working on
the University computers for this work. You will be using more specialised R
packages than you might be used to. This is especially important if you often
have difficulty updating and or installing software on your own machine,
wouldn't know what what version of R you are using or don't realise
there is a difference between R and RStudio. The uni machines always
have up-to-date R and R packages and all the packages that appear in
teaching materials. It is my responsibility to ensure everything works on here.

You can still work from home by using the [Virtual Desktop Service](https://www.york.ac.uk/it-services/tools/vds/). The VDS allows you
to log on to a university computer from your own computer. It means you can
access all software and filestores. When using the VDS for R and RStudio,
it usually makes sense to use other software - such as a browser or file
explorer - also through the VDS.

If you are confident in your ability to set up your own machine, you need:

- to know the difference between R and RStudio
- to use R 4.4 and RStudio 2024.09.0 Build 375 ("Cranberry Hibiscus")
- be certain you are actually using R 4.4 - it is written in the top edge
of the console window. By default RStudio uses the latest version on
R on your machine. However, windows users are able to change this
to a "specific version". You might have done that previously. Change it
back using Tools | Global Options R version "Use your machine's default
64-bit version of R"
- to make sure you do the independent study where it tells you what steps
you need to take to get packages (and versions that are unlikely to
cause issues) used in the workshop

It is possible to access all your files on your university account without
using the VDS. For example, if you want to work on uni machines at uni
and your machine at home. You can best do this by mapping a drive: https://support.york.ac.uk/s/topic/0TO4K000000lA5ZWAU/filestores.
If you store everything on google drive you can also read/write to that
like any other drive using google drive app.


Even if you plan to use your own machine I really recommend you take
the time to set the VDS up now while you're not time pressured so you always have that option ready.

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