Workshop & Seminar Series

Pre-workshop — Docker Installation Support

Optional session to help participants install and verify Docker before the hands-on training begins.

Session 1 — From Reads to Biology: An Introduction to Bulk RNA-seq

• What RNA-seq measures: biological rationale and technical principles
• Sequencing depth: what target depth means and how it is decided
• From reads to biology: quality assessment, quantification, normalization, differential expression, and functional annotation

Session 2 — Anatomy of Sequencing Data Formats

• Structure and purpose of the standard sequencing data formats
• How reference sequences, reads, alignments, and expression estimates are each encoded
• Which format belongs at which stage of an analysis

Hands-on

• Inspect a FASTA reference and FASTQ records, and interpret quality encoding
• Examine BAM alignment records, flags, and CIGAR strings
• Trace one gene from its alignment records through to its expression value

Session 3 — From FASTQ to Counts: Alignment and Quantification

• End-to-end preprocessing and gene expression quantification
• Reference preparation, genome indexing, and spliced read alignment
• Alignment-based versus alignment-free approaches, and when each is appropriate

Hands-on

• Build a genome index from a reference sequence and gene annotation
• Align paired-end reads and review the mapping statistics
• Quantify transcript expression and inspect the resulting table

Session 4 — From Counts to Differences: Normalization and Differential Expression

• Why raw counts cannot be compared directly: library size, composition, and RNA quality
• Gene filtering, between-sample normalization, and the mean–variance relationship
• Accounting for covariates, moving from single genes to gene sets, and what multiple-testing correction protects against

Hands-on

• Filter low-expressed genes and normalize a count matrix so that samples become comparable
• Adjust for RNA quality and sex, then identify which experimental factors the data actually separates on
• Test which genes differ between disease and control, weighing effect size against statistical significance
• Score whole gene sets sample by sample, and find the biological processes that shift with disease

Session 5 — From Signatures to Prediction: Building a Sample Classifier

• Supervised versus unsupervised analysis, and what each can and cannot answer
• Training, testing, and cross-validation: why held-out samples are not optional
• Feature selection, and how to read accuracy, sensitivity, and specificity

Hands-on

• Hold out a test set and train a model that predicts diagnosis from expression alone
• Extract the compact gene signature the model selects, and examine how it separates the samples
• Evaluate accuracy, sensitivity, and specificity, then validate in a second brain region

Q & A

Final discussion, questions, and workshop wrap-up.

Pre-workshop — Docker Installation Support

Optional session to help participants install and verify Docker before the hands-on training begins.

Session 1 — Introduction to 16S rRNA Amplicon Sequencing

• Biological rationale and technical principles of 16S rRNA amplicon sequencing
• Structure of sequencing data, common experimental designs, and key terminology
• Conceptual foundation for hands-on data analysis in subsequent sessions

Session 2 — Introduction to R for Bioinformatics

Hands-on

• R programming environment for bioinformatics data analysis
• Foundational R syntax, data structures, and essential packages used in microbiome workflows
• Preparation to follow and reproduce analysis steps in later sessions

Session 3 — 16S rRNA Data Preprocessing

• End-to-end preprocessing using a containerized workflow
• Quality control, adapter trimming, denoising, and ASV inference
• Feature table generation as the primary output for downstream analysis

Hands-on

• Inspect raw FASTQ files and assess read quality
• Run quality control and denoising using the provided Docker workflow
• Generate and review the ASV feature table and representative sequences

Session 4 — Taxonomic Assignment, Analysis & Visualization

• Approaches for assigning taxonomy to ASVs and interpreting community composition
• Alpha and beta diversity metrics, differential abundance analysis
• Publication-ready visualization in R

Hands-on

• Assign taxonomy to ASVs using a reference database
• Compute and visualize alpha and beta diversity metrics
• Generate publication-ready figures using R

Q & A

Final discussion, questions, and workshop wrap-up.

• Making AI Work for Biomedical Research: Understanding Its Capabilities
• Setting Up and Tailoring AI for Biomedical Research: Practical Tips for Effective Use

Pre-workshop — Login Support

Optional session to confirm laptop connectivity to the demo server before the main program begins.

Session 1 — Linux Foundations for HPC

• Filesystem navigation, paths, file and directory management
• Safe command-line practices for shared environments

Hands-on

Session 2 — HPC Architecture & Permissions

• Login nodes, compute nodes, shared storage structure
• Permissions, ownership, group structure for collaborative work
• Project organization, README documentation, symbolic links

Hands-on

Session 3 — Using HPC Effectively with Slurm

• Job scheduling fundamentals: resource requests, submission, monitoring
• Running bioinformatics analyses as scalable scheduled workflows

Hands-on

Capstone Exercise

Create a structured project directory, submit a Slurm job that calculates factorials using R or Python, verify output, and copy results to a shared folder with correct permissions.

Q & A

Final discussion, questions, and workshop wrap-up.