Day 1 – Thursday, June 26
11:00
12:00 LUNCH
13:00 Course Introduction
14:00 Break
14:15 Defining your RNA-seq strategy
15:15 Break
15:30 Introduction to high-throughput data analysis
16:30 Break
16:45 Package Loading
18:00 DINNER
Day 2 – Friday, June 27
11:00 RCR
12:00 LUNCH
13:00 Introduction to R Studio
14:00 Break
14:15 Introduction to R data types
15:15 Break
15:30 R logic loops and functions
16:30 Break
16:45 Promises and challenges of next-generation sequencing in contemporary biology
18:00 DINNER
Day 3 – Saturday, June 28
11:00 UNIX Files and Directories
12:00 LUNCH
13:00 UNIX Jobs and Processes
14:00 Break
14:15 Pre-processing RNA-seq data with fastp
15:15 Break
15:30 Quantification with salmon
16:30 Break
16:45 Collaborative open research: lessons learned from working reproducibly with others
18:00 DINNER
Day 4 – Sunday, June 29
11:00 Gene ID Conversion in R
12:00 LUNCH
13:00 Exploratory data analysis and normalization of transcriptomic data
14:00 Break
14:15 edgeR and differential gene expression
15:15 Break
15:30 Over-representation analysis
16:30 Break
16:45 R Markdown and R Notebook
18:00 DINNER
Day 5 – Monday, June 30
11:00 GSEA and pathway activation analysis
12:00 LUNCH
13:00 Online tools for gene set and pathway analysis
14:00 Break
14:15 Hands-on machine learning in R
15:15 Break
15:30 Choosing a machine learning approach to match your research question
16:30 Break
16:45 Rigor and reproducibility in machine learning
18:00 DINNER
Day 6 – Tuesday, July 1
11:00 Group Project – RNA-seq data reanalysis
12:00 LUNCH
13:00 Group Project – RNA-seq data reanalysis
14:00 Break
14:15 Group Project – RNA-seq data reanalysis
15:15 Break
15:30 Group Project – RNA-seq data reanalysis
16:30 DINNER
16:45 Group Project – Presentations
18:00
Day 7 – Wednesday, July 2
11:00 Overview of rigor and reproducibility
12:00 LUNCH
13:00 Tools to access publicly available transcriptomic databases
14:00 Break
14:15 Data Cleaning
15:15 Break
15:30 Philosophy of Statistics
16:30 Break
16:45 Workflows for the integration of Human and Mouse Multiomics Data
18:00 DINNER
Day 8 – Thursday, July 3
11:00 Using R for Basic Laboratory Statistics and Graphs
12:00 LUNCH
13:00 Correlation Analysis
14:00 Break
14:15 Models and Scientific Inquiry (lm)
15:15 Break
15:30 Analysis of Cytokine Data in R
16:30 Break
16:45 Testing for Associations in Count Data in R
18:00 DINNER
Day 9 – Friday, July 4 – HOLIDAY
Day 10 – Saturday, July 5
11:00 PCR Analysis in R
12:00 LUNCH
13:00 Model-Based Normalization in R
14:00 Break
14:15 Introduction to ggplot geometries and statistics
15:15 Break
15:30 Analysis of Cytokine Data in R
16:30 Break
16:45 FREE
18:00 DINNER
Day 11 – Sunday, July 6
11:00 Beyond the Bar – Dendextend and ComplexHeatmap
12:00 LUNCH
13:00 Beyond the Bar – FactoExtra
14:00 Break
14:15 Pirate plot and corrplots
15:15 Break
15:30 Chartering your way to better R Code – LLMs as Copilots
16:30 Break
16:45 Using LLM to Replicate Published Analyses
18:00 DINNER
Day 12 – Monday, July 7
11:00 Writing a data management plan
12:00 LUNCH
13:00 Reanalysis of publicly available data on a shiny web server
14:00 Break
14:15 Public repositories for ‘omics data
15:15 Break
15:30 Sharing metadata – how to annotate your experience
16:30 Break
16:45 The human microbiome in health and disease
18:00 DINNER
Day 13A – Tuesday, July 8
11:00 Introduction to single-cell RNA-seq
12:00 LUNCH
13:00 Cell QC and filtering
14:00 Break
14:15 Feature selection and clustering
15:15 Break
15:30 Normalization, dimension reduction, and visualization
16:30 Break
16:45 The human microbiome in health and disease
18:00 DINNER
Day 13B – Tuesday, July 8
11:00 Introduction to microbiome analysis and experiment design
12:00 LUNCH
13:00 Denoising and QC Filtering with Cutadapt and DADA2
14:00 Break
14:15 Microbiome Data Prep: Trimming fastq files, merging paired fastq files with DADA2
15:15 Break
15:30 Microbiome Data Prep: Silva taxonomic reference and building ASV counts data frame with DADA2, looking at metadata/sample info data frame
16:30 Break
16:45 FREE
18:00 DINNER
Day 14A – Wednesday, July 9
11:00 Clustering, cluster markers, and cell identity prediction
12:00 LUNCH
13:00 Exploring a pre-processed single-cell RNA-seq dataset from a publication
14:00 Break
14:15 TBD
15:15 Break
15:30 Sample integration and differential expression analysis
16:30 Break
16:45 FREE
18:00 LOBSTER BAKE
Day 14B – Wednesday, July 9
11:00 Microbiome Data Analysis: Building physloeq object. Applying ggplot language/tools to look at alpha diversity and beta diversity.
12:00 LUNCH
13:00 Microbiome Data Analysis: Normalizing for Relative abundance, log2 fold change, making relative abundance plots
14:00 Break
14:15 Microbiome Data Analysis: Statistics for each type of plot we’ve made (alpha, beta, relative abundance)
15:15 Break
15:30 Microbiome Data Analysis: Training a random forest model from gut microbiome data
16:30 Break
16:45 FREE
18:00 LOBSTER BAKE
Day 15– Thursday, July 10
Graded Presentations
