Gene Set Analysis in R (7:43) - Module 4 | Coursera

Gene Set Analysis in R (7:43)

video-placeholder

Loading...

基因组数据科学所需的统计学

约翰霍普金斯大学

4.2（319 個評分）

|

30K 名學生已註冊

課程 6（共 6 門，基因组数据科学專項課程）

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.

查看授課大綱

您將學習的技能

Statistics, Data Analysis, R Programming, Biostatistics

審閱

4.2（319 個評分）

5 stars
54.54%
4 stars
26.95%
3 stars
11.28%
2 stars
2.50%
1 star
4.70%

TK

2019年3月24日

Very good course and useful understanding statistical aspects of data.

HD

2021年4月8日

This is the best. It opens my eye for genomic data analysis.

從本節課中

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

教學方

Jeff Leek, PhD
Associate Professor, Biostatistics

以免費的價格試聽課程

探索我們的目錄

免費加入並獲得個性化推薦、更新和優惠。