BiocSwirl

BiocSwirl is a series of in-depth swirlify generated courses used to teach bioinformatics workflows in R/Bioconductor using an interactive and easy to digest format. This project was the People's Choice Award for the Vancouver Bioinformatics Hackathon Hackseq2019.

Install

Submission to Bioconductor pending.

# install.packages("devtools")
# library(devtools)
devtools::install_github("biocswirl-dev-team/BiocSwirl")
library(BiocSwirl)

Alternatively, the BiocSwirl courses can be installed independently. Please follow these instructions to manually install our courses: https://github.com/swirldev/swirl_courses/wiki/Legacy-Manual-Install-Instructions-for-Swirl-Courses

Background

There have been many resources available to interdisciplinary researchers for years now in the form of Rbookdown tutorials, in person workshops, and Youtube videos. However, each method of learning has its pros and cons - for blogpost and video type tutorials we have the inability to troubleshoot and raise our hands, for in-person workshops we have time limitations.

Bioinformatics has grown in adoption in many traditional non-computer science fields that lack the time and energy to go truly in depth past copying and pasting code found online. Swirlstats and terminal-based Python courses such as browser-based Codeacademy, have shown to be efficient course structures to teach data science and statistics to complete beginners.

We developed swirlify()-style console/terminal based courses for the purposes of teaching bioinformatics workflow steps and good coding practices. The philosophy is to keep the GUI use and application switching as minimal as possible but the content itself very rich and informative.

See also for out interface companion to the course materials. The interface (BiocTerm) and R package (BiocSwirl) can be used independently of each other but are best used together for people who are interested in making the most of their learning experience.

To view a demo, see here

Features

BiocSwirl includes

• Interactive course material that goes from beginner's steps (package installation and environment setup) to low level, to high level analyses and visualizations

• Is easily configurable and breaks down complex bioinformatics workflows into simple, easy to chew steps. Includes standardized datasets to work with and checks your work

• Highly emphases good coding practices, open science, reproducibility, and YAML file format and templates make it easy to update a workflow to match current best practices and create/communicate your own workflows for within lab

• Example inputs and outputs

• Course-specific package installations and standardized datasets

• Ability to start at any point of the course material

• Ability to save progress

• Compatability with BiocTerm

• Lightweight install, you can install what you want and included datasets are not large. Processing of data is not resource heavy and so it will work on low spec systems

Pending:

• Templates to communicate own workflow in notebook style
• Multilanguage workflow course materials for use with BiocTerm
• More courses
• Output checker/"Smart Marker"

Examples of use (GSE71585 dataset):

• Low Level Analyses
  a. Importing, raw data preprocessing
  b. Alignment
  c. Quality Control
  d. Normalization (with and without spike-ins)
  e. Dimensionality Reduction
  f. Correcting for batch effects
• High Level Analyses
  a. Clustering methods, exploratory analyses
  b. Cell cycle phase classification from gene expression data
  c. HVG and marker gene identification
• Visualizations for high-throughput data

Current courses available

Further reference:

Vignette - Install/Uninstall/Start Courses

Publication

coming soon.

Contributing

We are always looking for pull requests and active contributors, if you are interested in designing a course for us or have a feature in mind please submit an issue before doing a pull request. We are currently looking for help developing on Windows systems, bioinformatics workflows and concepts, and support for even more languages in BiocTerm.

Current & Previous Contributers:

Name	GitHub ID	Work done
Lisa N. Cao	lisancao	User Environment & Interface Development
Jackie Lu	jql6	User Environment & Interface Development
Jeremy Fan	zhemingfan	User Environment & Interface Development
Mariam Arab	mariamarab	User Environment & Installation
Kate Tyshchenko	ktyshchenko	Documentation, Course Material
Paaksum Wong	paaksum	Course Material (main)
Sourav Singh	souravsingh	Course Material
Julia Philipp	JuliaPhilipp	Manuscript & Couse Development
Matthew Moss	mmoss609	Course Development
Almas Khan	almas2019	Course Development
Denitsa Vasileva	deni678	Course Development
Jasdeep Singh		Course Development
Nicolai von Kügelgen	Nicolai-vKuegelgen	Course Development
Elizabeth Hutchins	e-hutchins	Course Development
Benson Lee	bensonlee5	User Environment & Interface Development

Details about hackseq19 project Details about CSHL codeathon project