This reproducible R Markdown
analysis was created with workflowr (version
1.7.1). The Checks tab describes the reproducibility checks
that were applied when the results were created. The Past
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Great! You are using Git for version control. Tracking code development
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The results in this page were generated with repository version
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See the Past versions tab to see a history of the changes made
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These are the previous versions of the repository in which changes were
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past version.
We’ll drop resources that we find
that might be useful to others.
Coding and Single cell crash course
From a single cell and spatial analysis course by Cold Spring Harbour
Laboratory, these resources are great for both total beginners to coding
and analysis to those starting to analyse their own data.
This is the Basics
of Linux/Shell and R where you how to navigate through your Terminal
and the start of your R journey.
Processing
scRNA and Visium HD can be daunting but this breaks down all the
steps you need to clean, cluster, and visualise your data, as well as
the theory behind it.
Computational Genomics with R
Computational Genomics
with R is an exceptionally comprehensive resource for biomedical
bioinformatics. It covers a broad range of topics—statistics, machine
learning, sequencing data processing, and more—while providing both code
examples and clear explanations. Although it may not be the most
accessible starting point for wet-lab researchers, it serves as an
invaluable reference for deeper explorations of bioinformatic
analyses.
10X Analysis Resources
10X Genomics are a unique company, in that they provide a
lot of supporting materials. In the drop down below, we have listed
a series of resources that 10X have provided, including how-to videos
and tutorials.
Stretchly is an
open-source app designed to encourage healthy work habits by prompting
regular short (30-second) and long (20-minute) breaks. I’ve found it
invaluable for maintaining focus and preventing burnout. It’s highly
customizable, allowing you to tailor prompts to your needs.
roadmap.sh
roadmap.sh provides structured
learning pathways for various tech-related skills, from Data Science to
DevOps. The Data Science and AI roadmap outlines essential topics such
as mathematics, statistics, and coding, along with curated free and paid
learning resources. These roadmaps are community-driven and frequently
updated, making them a great guide for self-paced learning.
LinkedIn Learning
LinkedIn Learning
offers a vast library of online courses covering data analysis,
programming (including R and Python), statistics, research skills, and
professional development. There is a short R
for Data Science course that is quite nice.
You should have access to LinkedIn Learning through your University
email. Otherwise, WIMR staff can apply for a license through WIMR.
Sydney Informatics Hub
Sydney Informatics Hub offers training
workshops regularly on research data management, statistical
methods, and high-performance computing. These are more general methods
that not only apply to biomedical research, but may provide inspiration
or good fundamental knowledge on the analytical methods we use.
Interactive R learning UI
learnr is a package that you
can install which provides a nice little UI if you want to practice
basicR skills and prefer some interactivity.
ggplot2 book
ggplot2:Elegant
Graphics for Data Analysis is a nice, comprehensive handbook for
graphing using ggplot2. It covers the basic layout, different graph
types, customizing elements such as colours, group overlays,
annotations, etc.
