FAIR Bioinformatics 2023

FAIR Bioinformatics Course – 2023

Click the links below to access full recordings of the 2023 FAIR Bioinformatics Course.

Introduction to High-Throughput Data Analysis (Thomas Hampton, Ph.D.)

Defining your RNA-seq strategy (Kelley Thomas, Ph.D.)

Evening Seminar: “Promise and Challenges of Next-Generation Sequencing in Contemporary Biology.”

Basic R: Logic, Loops and Functions (Sam Neff)

Basic R: Data Types, Exploratory Statistics and Graphs (Sam Neff)

Introducing R Studio (Sam Neff)

Responsible Conduct of Research (Jane Disney, Ph.D.)

Evening Seminar: “Collaborative Open Research: Lessons Learned from Working Reproducibly with Others.”

Scripts – Files That Are Programs (Kiyoshi Fukutani, Ph.D.)

Unix Jobs and Processes (Kiyoshi Fukutani, Ph.D.)

Unix Files and Directories (Kiyoshi Fukutani, Ph.D.)

edgeR and Differential Gene Expression (Lily Charpentier)

Exploratory Data Analysis and Normalization of Transcriptomic Data (Lily Charpentier)

Gene ID Conversion in R (Zhongyou Li, Ph.D.)

Quantification with Salmon (fastp and salmon exercise, tximport exercise, slides) (Jaclyn Taroni, Ph.D.)

Online Tools for Gene Set and Pathway Analysis (Zhongyou Li, Ph.D.)

GSEA and Pathway Activation Analysis (Zhongyou Li, Ph.D.)

Analysis of Contingency tables (Todd MacKenzie, Ph.D.)

Over-representation Analysis in R (Zhongyou Li, Ph.D.)

Evening Seminar: “How data drives translational medicine in drug development.”

Hands on Machine Learning in R (Thomas Hampton, Ph.D.)

Machine Learning II: Unsupervised ML for biological contexts (Jaclyn Taroni, Ph.D.)

Machine Learning I: Introduction to experimental design (slides) (Jaclyn Taroni, Ph.D.)

Data Cleaning and Merging Multiple Datasets (Zhongyou Li, Ph.D.)

Overview of Rigor and Reproducibility (Bruce Stanton, Ph.D.)

Tools to Access Publicly Available Transcriptomic Databases (Zhongyou Li, Ph.D.)

Findability, Accessibility, Interoperability, and Reusability in the Biomedical Context (Andrew Creamer) 

Evening Seminar: “Managing Workflows for Multiomics Data”

Statistical Modeling for Research Scientists (Todd Mackenzie, Ph.D.)

Linear Models (Data) (Todd Mackenzie, Ph.D.)

Common ggplot Geometries and Statistics (Rebecca Valls) Part – II

Common ggplot Geometries and Statistics (Rebecca Valls) Part – I

Introduction to ggplot – Basic Syntax and Data Format (Rebecca Valls)

Factors That Make Transcriptomic Data Difficult to Reproduce (Tom Hampton, Ph.D.)

Principal Component Analysis (Tom Hampton, Ph.D.)

R Markdown (Lily Charpentier)

Pirate Plots and Corrplots (Lily Charpentier)

Beyond the Bar Graph: Making Complex Figures in R [Part 2: FactoExtra] (Sam Neff)

Beyond the Bar Graph: Making Complex Figures in R [Part 1: ComplexHeatmap] (Sam Neff)

Evening Seminar: “The Human Microbiome in Health and Disease.”

Sharing Meta-data: How to Annotate Your Experiment (Pamela Bagley, Ph.D.)

Public Repositories for ‘Omics Data (Carly Bobak, Ph.D.)

Reanalysis of Publicly Available Data on a Shiny Web Server (Zhongyou Li, Ph.D.)

Writing a Data Management Plan (Pamela Bagley, Ph.D.)

Hands-On Microbiome Analysis in R, Part 2: Sequence Processing with DADA2 (Rebecca Valls)

Hands-On Microbiome Analysis in R, Part 1: Introduction to Microbiome Analysis (Rebecca Valls)

Evening Seminar: “Statistical and Methodological Approaches to Increase the Reproducibility and Rigor of Single-Cell RNA-seq”

Single-Cell RNA-Seq Data Analysis in R Part 2: Normalization, dimension reduction, and visualization solutions (Britton Goodale, Ph.D.)

Single-Cell RNA-Seq Data Analysis in R Part 1: Cell QC and filtering solutions (Britton Goodale, Ph.D.)

Introduction to Single-Cell RNA-Seq (Britton Goodale, Ph.D.)

Hands-On Microbiome Analysis in R, Part 4: Statistics for Microbiome Data (Rebecca Valls).

Hands-On Microbiome Analysis in R, Part 3: Phyloseq Analysis (Rebecca Valls)

Single-Cell RNA-Seq Data Analysis in R Part 5: Sample integration and differential expression analysis (Britton Goodale, Ph.D.)

Single-Cell RNA-Seq Data Analysis in R Part 4: Exploring a pre-processed single cell RNA-seq dataset from a publication (Britton Goodale, Ph.D.)

Single-Cell RNA-Part 3: Clustering, cluster markers, and cell identity detection (Britton Goodale, Ph.D.)