Brainstorm lesson points, and organise them thematically, to facilitate the design of episodes.

See the episode Introduction to Bioconductor.

Topics:

• Mission statement and objectives
• Brief history of the Bioconductor project (e.g., timeline of milestones)
• Core publications of the Bioconductor project (i.e., core infrastructure, not research papers simply using Bioconductor packages)
• Relationship to the CRAN repository
• Release cycle
• Types of packages
• The Bioconductor main website
• The Bioconductor support website
• Package classification using biocViews
• Interoperability of Bioconductor packages
• Education: Conferences, workshops, courses, (online) books, YouTube channel
• Communication: support website, Slack workspace, developers mailing list
• Governance: Scientific, Technical, and Community Advisory Boards (i.e., SAB, TAB, and CAB)
• Code of Conduct (CoC) Committee
• Overview of packages in an analytical workflow

Challenges:

• Find information on the Bioconductor main website
• Explore software packages using biocViews on the Bioconductor main website
• Explore annotation packages using biocViews on the Bioconductor main website
• Explore workflow packages using biocViews on the Bioconductor main website

See the episode Installing Bioconductor.

Topics:

• Installing the BiocManager package
• Bioconductor releases and their relationship to R versions
• Versioning of Bioconductor packages
• The release and devel branches of the Bioconductor repository
• Installing Bioconductor packages
• Checking for package updates
• Updating Bioconductor packages
• Finding packages using biocViews

Challenges:

• Install BiocManager from CRAN

See the episode Getting help.

• Man pages (description, arguments, examples)
• Vignettes

• Package landing pages
• The Bioconductor main website
• Educational materials from courses and workshops
• Workflow packages and vignettes

• The Bioconductor support site
• Issues on source code repositories (e.g., GitHub)
• Why you should not email package developers directly

Challenges:

• TODO

No episode yet.

Topics:

• Common data structures: DNAStringSet, GRanges, GAlignments, SummarizedExperiment, TxDb
• Bioconductor Core Team
• Less redundancy
• More interoperability
• Stability: slow and thoughtful development
• Part of the review for new packages
• Classes and basic functionality implemented separately from data processing methods
• S4 is a formal definition of class slots and types
• S4 implements inheritance and validity checks

Challenges:

• TODO

See the episode Biostrings.

Topics:

• Motivation for representing biological strings as S4 objects
• Representing a single DNA string
• Importing a collection of DNA strings from a file
• Examples of methods available to process biological strings

Challenges

• Install the Biostrings package.
• Inspect the DNA_ALPHABET built-in object.
• Import a small set of DNA sequences from a FASTA file; inspect the class of the object.
• Use the letterFrequency() function. Compare with regular character string inputs.
• List the package vignettes and examine their contents.

No episode yet.

• The basilisk package