John Hopkins University - Statistics for Genomic Data Science 

Welcome to Statistics for Genomic Data Science

What is Statistics?

Finding Statistics You Can Trust (4:44)

Getting Help (3:44)

What is Data? (4:28)

Representing Data (5:23)

Module 1 Overview (1:07)

Reproducible Research (3:42)

Achieving Reproducible Research (5:02)

R Markdown (6:26)

The Three Tables in Genomics (2:10)

The Three Tables in Genomics (in R) (3:46)

Experimental Design: Variability, Replication, and Power (14:17)

Experimental Design: Confounding and Randomization (9:26)

Exploratory Analysis (9:21)

Exploratory Analysis in R Part I (7:22)

Exploratory Analysis in R Part II (10:07)

Exploratory Analysis in R Part III (7:26)

Data Transforms (7:31)

Clustering (8:43)

Clustering in R (9:09)

Syllabus

Pre Course Survey

Introduction and Materials

Module 1 Quiz

Module 2

Module 2 Overview (1:12)

Dimension Reduction (12:13)

Dimension Reduction (in R) (8:48)

Pre-processing and Normalization (11:26)

Quantile Normalization (in R) (4:49)

The Linear Model (6:50)

Linear Models with Categorical Covariates (4:08)

Adjusting for Covariates (4:16)

Linear Regression in R (13:03)

Many Regressions at Once (3:50)

Many Regressions in R (7:21)

Batch Effects and Confounders (7:11)

Batch Effects in R: Part A (8:18)

Batch Effects in R: Part B (3:50)

Module 2 Quiz

Module 3

Module 3 Overview (1:07)

Logistic Regression (7:03)

Regression for Counts (5:02)

GLMs in R (9:28)

Inference (4:18)

Null and Alternative Hypotheses (4:45)

Calculating Statistics (5:11)

Comparing Models (7:08)

Calculating Statistics in R

Permutation (3:26)

Permutation in R (3:33)

P-values (6:04)

Multiple Testing (8:25)

P-values and Multiple Testing in R: Part A (5:58)

P-values and Multiple Testing in R: Part B (4:23)

Module 3 Quiz

Module 4

Module 4 Overview (1:21)

Gene Set Enrichment (4:19)

More Enrichment (3:59)

Gene Set Analysis in R (7:43)

The Process for RNA-seq (3:59)

The Process for Chip-Seq (5:25)

The Process for DNA Methylation (5:03)

The Process for GWAS/WGS (6:12)

Combining Data Types (eQTL) (6:04)

eQTL in R (10:36)

Researcher Degrees of Freedom (5:49)

Inference vs. Prediction (8:52)

Knowing When to Get Help (2:31)

Statistics for Genomic Data Science Wrap-Up (1:53)

Post Course Survey

Module 4 Quiz