Combining Data Types (eQTL) (6:04) - Module 4 | Coursera

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基因组数据科学所需的统计学

约翰霍普金斯大学

4.2（284 个评分） | 26K 名学生已注册

课程 7（共 8 门，基因组数据科学专项课程）

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.

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您将学习的技能

Statistics, Data Analysis, R Programming, Biostatistics

审阅

4.2（284 个评分）

5 stars
54.22%
4 stars
26.76%
3 stars
11.26%
2 stars
2.81%
1 star
4.92%

TK

Mar 24, 2019

Very good course and useful understanding statistical aspects of data.

HD

Apr 8, 2021

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

从本节课中

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

教学方

Jeff Leek, PhD
Associate Professor, Biostatistics

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