Home > Learning > BI/DS Tutorials and Workshops > 2026 Summer Workshops
Embedded Files
SC INBRE Biostatistics Summer Courses 2026:
Week 3 – Bioinformatics & High-Dimensional Data
Three one-week courses were offered. Four hours/day – 10 am to 12 pm (lecture and discussion) and 1 to 3 pm (R lab and application). Morning sessions and course lab instructions were recorded.
Course Presenter: Dr. Alexander McLain, University of South Carolina Arnold School of Public Health, Professor of Epidemiology and Biostatistics
Courses
Week 1 (June 1-5): Foundations of Data Science in R
Week 2 (June 8-12): Statistical Modeling
Week 3 (June 15-19): Bioinformatics & High-Dimensional Data
Daily Schedule
10 am to 12 pm: Lecture and discussion
1 to 3 pm: R Lab and application
Links
WEEK 3 (June 15-19): Bioinformatics & High-Dimensional Data
Target: Genomics workflows, dimensionality reduction, penalized regression, and reproducible reporting.
Monday, June 15, Day 11
MORNING
Genomics Data: Structure, Formats, and Public Databases
FASTQ, BAM, VCF, count matrix formats; overview of NCBI/GEO/dbGaP; accessing public datasets; data provenance and metadata.
AFTERNOON
Accessing Public Genomics Data
Using GEOquery and Biobase to retrieve expression datasets; exploring metadata; quality assessment with basic EDA.
Tuesday, June 16, Day 12
MORNING
Differential Expression Analysis
RNA-seq workflow overview (alignment → counts → DE); negative binomial models; DESeq2/edgeR framework; normalization strategies.
AFTERNOON
DESeq2 Lab
Full DESeq2 workflow: importing count data, size factor normalization, dispersion estimation, Wald/LRT tests, results tables.
Wednesday, June 17, Day 13
MORNING
Multiple Testing, FDR, and Visualization of High-Dimensional Results
Family-wise error rate vs. FDR; Bonferroni, Benjamini-Hochberg; q-values; volcano plots; MA plots; heatmaps.
AFTERNOON
Multiple Testing & Visualization Lab
Applying p.adjust(); generating volcano and MA plots with ggplot2; hierarchical clustering and heatmaps with pheatmap/ComplexHeatmap.
Thursday, June 18, Day 14
MORNING
Dimensionality Reduction and Penalized Regression
PCA and its geometric interpretation; scree plots; biplots; introduction to LASSO/ridge/elastic net; coordinate descent; tuning λ.
AFTERNOON
PCA and glmnet Lab
prcomp() and factoextra for PCA; fitting penalized regression with glmnet; cross-validated λ selection; coefficient path plots; interpreting sparse solutions.
Friday, June 19, Day 15
MORNING
Reproducible Research and Course Capstone
R Markdown / Quarto for reproducible reporting; literate programming; project organization best practices; version control concepts.
AFTERNOON
Capstone Lab & Presentations
Students produce a short reproducible analysis report (R Markdown/Quarto) integrating skills from the course; brief group presentations and discussion.
No recording due to Juneteenth federal holiday and Capstone project presentations
Page updated June 19, 2026
Page updated
Google Sites
Report abuse