FAIR 2024 Recordings
Thomas, K: Defining your RNA-seq strategy
Hampton: Introduction to high-throughput data analysis
Disney: Responsible conduct of research
Charpentier: Introduction to R Studio
Charpentier: Intro to R data types
Charpentier: R logic loops and functions
Thomas, K: Promises and challenges of next-generation sequencing in contemporary biology
Fukutani: UNIX Files and Directories
Fukutani: UNIX Jobs and Processes
Taroni: Pre-processing RNA-seq data with fastp and Quantification with salmon
Taroni: Collaborative open research: lessons learned from working reproducibly with others
Charpentier: Exploratory data analysis and normalization of transcriptomic data
Charpentier: edgeR and differential gene expression
Li: Over-representation analysis
Li: GSEA and pathway activation analysis
Li: Online tools for gene set and pathway analysis
Taroni: Choosing a machine learning approach to match your research question
Taroni: Rigor and reproducibility in machine learning
Hampton: Hands-on machine learning in R
Stanton: Overview of rigor and reproducibility
Li: Tools to access publicly available transcriptomic databases
Hampton: Philosophy of Statistics
Churchill: Workflows for the Integration of Human and Mouse Multiomics Data
Hampton: Using R for Basic Laboratory Statistics and Graphs
MacKenzie: Models and Scientific Inquiry (lm)
Hampton: Analysis of Cytokine Data in R
MacKenzie: Testing for Associations in Count Data in R
MacKenzie: Model-Based Normalization in R
Valls, Hilliam: Introduction to ggplot – basic syntax and data format
Valls, Hilliam: Common ggplot geometries and statistics
Neff: Beyond The Bar – Dendextend and ComplexHeatmap
Neff: Beyond The Bar- FactoExtra
Charpentier: Pirate plot and corrplots
Bobak: Chartering your way to better R Code – LLM’s as Copilots
Bobak: Using LLM to Replicate Published Analyses
Bagley: Writing a data management plan
Taub: Reanalysis of publicly available data on a shiny web server
Bobak: Public repositories for ‘omics data
Bagley: Sharing metadata – how to annotate your experiment
Oh: The human microbiome in health and disease
Goodale: Introduction to single-cell RNA-seq
Goodale: Data QC, filtering, and normalization
Goodale: Feature selection and clustering
Goodale: Clustering, cluster markers and cell identity prediction
Goodale: Exploring a pre-processed single cell RNA-seq dataset from a publication
Goodale: Sample integration and differential expression analysis
Valls, Hilliam: Introduction to microbiome experiment design and analysis
Valls, Hilliam: Using DADA 2 for QC filtering, trimming and merging
Valls, Hilliam: Building a phyloseq object and Decontam
Valls, Hilliam: Visualizing and analyzing alpha diversity, beta diversity, and relative abundance