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Achieving Reproducible Research (5:02)

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From the course by Johns Hopkins University
Statistics for Genomic Data Science
140 ratings
Johns Hopkins University

Statistics for Genomic Data Science

140 ratings
Course 7 of 8 in the Specialization Genomic Data Science
From the lesson
Module 1
This course is structured to hit the key conceptual ideas of normalization, exploratory analysis, linear modeling, testing, and multiple testing that arise over and over in genomic studies.
Module 1 Overview (1:07)1:07
Reproducible Research (3:42)3:42
Achieving Reproducible Research (5:02)5:02
R Markdown (6:26)6:26
The Three Tables in Genomics (2:10)2:10
The Three Tables in Genomics (in R) (3:46)3:46
Experimental Design: Variability, Replication, and Power (14:17)14:17
Experimental Design: Confounding and Randomization (9:26)9:26
Exploratory Analysis (9:21)9:21
Exploratory Analysis in R Part I (7:22)7:22
Exploratory Analysis in R Part II (10:07)10:07
Exploratory Analysis in R Part III (7:26)7:26
Data Transforms (7:31)7:31
Clustering (8:43)8:43
Clustering in R (9:09)9:09

Meet the Instructors

  • Jeff Leek, PhD
    Jeff Leek, PhD
    Associate Professor, Biostatistics
    Bloomberg School of Public Health

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