Statistics for Genomic Data Science Wrap-Up (1:53) - Module 4 | Coursera

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

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Statistics for Genomic Data Science

Johns Hopkins University

4.2 (303 ratings)

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28K Students Enrolled

Course 6 of 6 in the Genomic Data Science Specialization

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An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Skills You'll Learn

Statistics, Data Analysis, R Programming, Biostatistics

Reviews

4.2 (303 ratings)

5 stars
54.45%
4 stars
27.39%
3 stars
10.56%
2 stars
2.64%
1 star
4.95%

CJ

Jul 15, 2019

It is really great that told me lots of basic statistical information that I didn't know.

TK

Mar 24, 2019

Very good course and useful understanding statistical aspects of data.

From the lesson

Module 4

In this week we will cover a lot of the general pipelines people use to analyze specific data types like RNA-seq, GWAS, ChIP-Seq, and DNA Methylation studies.

Module 4 Overview (1:21)1:21

Gene Set Enrichment (4:19)4:19

More Enrichment (3:59)3:59

Gene Set Analysis in R (7:43)7:43

The Process for RNA-seq (3:59)3:59

The Process for Chip-Seq (5:25)5:25

The Process for DNA Methylation (5:03)5:03

The Process for GWAS/WGS (6:12)6:12

Combining Data Types (eQTL) (6:04)6:04

eQTL in R (10:36)10:36

Researcher Degrees of Freedom (5:49)5:49

Inference vs. Prediction (8:52)8:52

Knowing When to Get Help (2:31)2:31

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

Taught By

Jeff Leek, PhD
Associate Professor, Biostatistics

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