pgr_reproducibility

Training programme for first year PhD students on the White Rose Universities (York, Sheffield, Leeds). DTP

https://github.com/3mmarand/pgr_reproducibility

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Training programme for first year PhD students on the White Rose Universities (York, Sheffield, Leeds). DTP

README.html

Introduction to Reproducibility in R





Training programme for first year PhD students on the White Rose
Universities (York, Sheffield, Leeds) DTP. It is designed and delivered
by Emma
Rand of The University of York.

Overview
An increase in the complexity and scale of biological data means
biologists are increasingly required to develop the data skills needed
to design reproducible workflows for the simulation, collection,
organisation, processing, analysis and presentation of data. Developing
such data skills requires at least some coding, also known as scripting.
This makes your work (everything you do with your raw data) explicitly
described, totally transparent and completely reproducible. However,
learning to code can be a daunting prospect for many biologists! That’s
where an Introduction to
reproducible analyses in R comes in!
R is a free and open source language especially well-suited to data
analysis and visualisation and has a relatively inclusive and
newbie-friendly community. R caters to users who do not see themselves
as programmers, but then allows them to slide gradually into
programming.


Prerequisites
I recognise that people will enter this training with a diverse range
of previous experience in R. This is a challenge to manage but the aim
is for everyone to get something out of the training no matter where
they start. There will be sessions for those with and without previous
experience. I recommend you:

sit close to the front of the class if you are completely new to R
and towards the back if you have some experience
bring headphones to allow you to ignore tutor-led material when
needed

Pre-course instructions for participants are given below.


Philosophy and approach
It is impossible to cover everything to you might ever need!
Different people will use different methods and tools. Topics have been
chosen because they are: foundational, widely applicable and
transferable conceptually.


Learning outcomes
After this workshop the successful learner will be able to:

Find their way around the RStudio windows
Create and plot data using the base package and ggplot
Explain the rationale for scripting analysis
Use the help pages
Know how to make additional packages available in an R session
Understand what is meant by the working directory, absolute and
relative paths and be able to apply these concepts to data import
Summarise data in a single group or in multiple groups
Recognise tidy data format and carry out some typical data tidying
tasks
Develop highly organised analyses including well-commented scripts
that can be understood by future you and others
Use Quarto to produce reproducible analyses, figures and
reports



Schedule for workshop
1015 - 1035 Tutor-led for Everyone: Introduction
and Principles of reproducibility
1035 - 1200
Either:

Tutor-led for Beginners: Introduction
to R and working with data or
Supported learning for those with some R experience Tidying
data and the tidyverse including the pipe

1200 - 1300 Lunch
1300 - 1330

Tutor-led for Everyone: Project-oriented
workflow
1330 - 1445

Tutor-led for Everyone: Quarto for Reproducible Reports
1515 - 1515 Tea and coffee break
1515 - 1645

Continuation Quarto for Reproducible Reports


Pre-course instructions for participants

Precourse survey
To help me direct you to useful training and manage diversity in
previous experience during the sessions, please complete this form to
indicate your current level: https://forms.gle/cpSjdcjVa7niz6iq5


Facilities
There are Windows PCs at the venue and you are not required to bring
your own machine. Participants from outside of York will be provided
with a temporary IT account. However, if you prefer to work on your own
machine please follow the instructions in below



Computing requirements
If you decide to use your own laptop, please install the following
before the workshop. If you have any problems with
installation, please use the computers provided at the venue.

R version R-4.3. https://cloud.r-project.org/
RStudio Desktop (1.4) https://posit.co/download/rstudio-desktop/
OS-specific development tools:

Windows: Rtools https://cran.r-project.org/bin/windows/Rtools/
Mac: Xcode https://developer.apple.com/xcode/

these packages from CRAN: devtools,
tidyverse,
janitor Once you have installed R and
RStudio, start RStudio up and go to the Packages tab in the bottom right
pane; click Install and type the name of the package you want to install
in the box that appears. Then wait until you get the cursor (>) back
in the console window and install the next package.


Materials

White Rose
BBSRC Doctoral Training Partnership (DTP) in Mechanistic Biology
Analytics 1: Introduction to reproducible analyses in R by Emma Rand is licensed under a
Creative
Commons Attribution-NonCommercial-ShareAlike 4.0 International
License.
Please cite as: Rand E. (2023). White Rose BBSRC DTP Training: An
Introduction to Reproducible Analyses in R (version v1.2). DOI: https://doi.org/10.5281/zenodo.3859818 URL: https://github.com/3mmaRand/pgr_reproducibility
You can obtain all the workshop materials by using the green ‘Clone
or download’ button above.

Owner

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  White Rose BBSRC DTP Training: An Introduction to
  Reproducible Analyses in R
message: >-
  If you use this material, please cite it using these
  metadata.
type: software
authors:
  - family-names: Rand
    given-names: Emma
    orcid: 'https://orcid.org/0000-0002-1358-8275'
    affiliation: University of York
identifiers:
  - type: doi
    value: 10.5281/zenodo.4701167
repository-code: 'https://github.com/3mmaRand/pgr_reproducibility'
abstract: >-
  Training programme for first year PhD students on the
  White Rose Universities (York, Sheffield, Leeds) DTP. It
  is designed and delivered by Emma Rand of The University
  of York.
license: >-
  Creative Commons Attribution-NonCommercial-ShareAlike 4.0
  International License
version: 1.2.6
date-released: '2024-06-27'

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