START HERE
Start with orientation and basic computer concepts, then choose a language and research route that fit your work. These are suggested branches, not a mandatory course or a promise of a complete analysis pipeline.
WHO THIS IS FOR
You do not need to arrive with code or software experience. You only need a biological question worth investigating.
THE FOUNDATION
The four cards move from orientation through basic computing to a shell and software environments. Each lesson states its format and prerequisites; biological data formats are an optional reference, not a required stop. HPC is a separate optional track below.
See how biological questions, data, tools, and interpretation fit together.
Build a mental model of files, folders, formats, and computing before using a shell.
Start with safe navigation; continue through Parts 2 and 3 only as you need those skills.
Practice isolating software before choosing one programming-language route.
Pick the language that suits your tools, collaborators, and analysis. You do not need to learn both before continuing; either route joins the shared statistics and study-design foundations.
A cluster is not a universal entrance requirement. If your institution provides access or your workload needs it, start with connection and follow the Slurm lessons; follow local policies.
Open the optional HPC trackLook up biological file formats when a particular input is unfamiliar; it is not a prerequisite before learning shell basics.
Open the data-formats referenceCHOOSE YOUR ROUTE
Once you've built the foundation, choose the topic that matches your research. These routes are starting points into related guides, labs, and templates, not complete end-to-end research pipelines.
Start with scRNA-seq basics and cell-level QC, then annotation. Integration, multimodal analysis, and trajectory methods are optional branches for suitable inputs and questions.
Start with scRNA-seqCall variants from whole-exome or whole-genome sequencing, annotate mutations, and explore long-read data.
Start with WESProfile microbial communities, assemble metagenomes, and discover functional pathways in your samples.
Start with 16S rRNABuild phylogenies, identify orthologs, and explore genome-scale evolutionary relationships.
Start with PhylogenyROADMAP & REQUIREMENTS
Start small, then check each lesson for its own software, data, and computing needs.
A modern laptop is enough for many foundation exercises.
Check the chosen lesson's operating-system and memory requirements; needs vary with the tools and input size.
Larger analyses may need HPC or other high-memory computing. Estimate memory, storage, threads, and runtime for the actual data and tools; follow your institution's scheduler policies.
Install only what your chosen lesson asks for.
Follow the lesson's versions and dependencies. The collection is not standardized on one Python or R version. Record your environment and check compatibility.
Build the habit of planning, adapting, and checking reproducible analysis.
Complete the Command-Line Part 1 lab. Make a disposable project tree, safely copy and move files, and inspect the named zero-byte placeholders; confirm they are not sequencing data.
Check the displayed paths and file sizes. The lesson explains what each output verifies and what it cannot establish; practice templates are not research findings.
CHOOSE A ROUTE
Suggested routes, not a fixed course. Follow the branch that fits your data and question.
Build the foundations, choose R or Python, then rejoin at statistics and study design.
Pseudobulk differential expression
For suitable replicated scRNA-seq designs; not bulk RNA-seq.
Check cell-level quality before annotation; add methods only when the data and question support them.
Downstream analysisCommunicationTrajectory
Trajectory is optional; use it for a plausible continuous process.
Follow the DNA assay and its reference; WES is its own branch, not a single-cell route.
HPC is not required to start. Use it only with authorized access and a workload that needs it.
Follow your institution's security and scheduler policies.
If you already know the basics, choose a question-led route or use the full catalogue. HPC knowledge is not required to browse or begin. Check each page’s learning-format label: some are guided labs; others explain concepts, provide adaptable templates, or serve as references.
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