Об этом курсе
4.1
Оценки: 133
Рецензии: 25
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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Approx. 17 hours to complete

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Приобретаемые навыки

StatisticsData AnalysisR ProgrammingBiostatistics
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Гибкие сроки

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Approx. 17 hours to complete

Предполагаемая нагрузка: 6 hours/week...
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English

Субтитры: English...

Программа курса: что вы изучите

Week
1
Clock
3 ч. на завершение

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. ...
Reading
21 видео (всего 129 мин.), 3 материалов для самостоятельного изучения, 1 тест
Video21 видео
What is Statistics?2мин
Finding Statistics You Can Trust (4:44)4мин
Getting Help (3:44)3мин
What is Data? (4:28)4мин
Representing Data (5:23)5мин
Module 1 Overview (1:07)1мин
Reproducible Research (3:42)3мин
Achieving Reproducible Research (5:02)5мин
R Markdown (6:26)6мин
The Three Tables in Genomics (2:10)2мин
The Three Tables in Genomics (in R) (3:46)3мин
Experimental Design: Variability, Replication, and Power (14:17)14мин
Experimental Design: Confounding and Randomization (9:26)9мин
Exploratory Analysis (9:21)9мин
Exploratory Analysis in R Part I (7:22)7мин
Exploratory Analysis in R Part II (10:07)10мин
Exploratory Analysis in R Part III (7:26)7мин
Data Transforms (7:31)7мин
Clustering (8:43)8мин
Clustering in R (9:09)9мин
Reading3 материала для самостоятельного изучения
Syllabus10мин
Pre Course Survey10мин
Introduction and Materials10мин
Quiz1 практическое упражнение
Module 1 Quiz20мин
Week
2
Clock
2 ч. на завершение

Module 2

This week we will cover preprocessing, linear modeling, and batch effects....
Reading
14 видео (всего 97 мин.), 1 тест
Video14 видео
Dimension Reduction (12:13)12мин
Dimension Reduction (in R) (8:48)8мин
Pre-processing and Normalization (11:26)11мин
Quantile Normalization (in R) (4:49)4мин
The Linear Model (6:50)6мин
Linear Models with Categorical Covariates (4:08)4мин
Adjusting for Covariates (4:16)4мин
Linear Regression in R (13:03)13мин
Many Regressions at Once (3:50)3мин
Many Regressions in R (7:21)7мин
Batch Effects and Confounders (7:11)7мин
Batch Effects in R: Part A (8:18)8мин
Batch Effects in R: Part B (3:50)3мин
Quiz1 практическое упражнение
Module 2 Quiz20мин
Week
3
Clock
2 ч. на завершение

Module 3

This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing....
Reading
15 видео (всего 86 мин.), 1 тест
Video15 видео
Logistic Regression (7:03)7мин
Regression for Counts (5:02)5мин
GLMs in R (9:28)9мин
Inference (4:18)4мин
Null and Alternative Hypotheses (4:45)4мин
Calculating Statistics (5:11)5мин
Comparing Models (7:08)7мин
Calculating Statistics in R9мин
Permutation (3:26)3мин
Permutation in R (3:33)3мин
P-values (6:04)6мин
Multiple Testing (8:25)8мин
P-values and Multiple Testing in R: Part A (5:58)5мин
P-values and Multiple Testing in R: Part B (4:23)4мин
Quiz1 практическое упражнение
Module 3 Quiz20мин
Week
4
Clock
2 ч. на завершение

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. ...
Reading
14 видео (всего 74 мин.), 1 материал для самостоятельного изучения, 1 тест
Video14 видео
Gene Set Enrichment (4:19)4мин
More Enrichment (3:59)3мин
Gene Set Analysis in R (7:43)7мин
The Process for RNA-seq (3:59)3мин
The Process for Chip-Seq (5:25)5мин
The Process for DNA Methylation (5:03)5мин
The Process for GWAS/WGS (6:12)6мин
Combining Data Types (eQTL) (6:04)6мин
eQTL in R (10:36)10мин
Researcher Degrees of Freedom (5:49)5мин
Inference vs. Prediction (8:52)8мин
Knowing When to Get Help (2:31)2мин
Statistics for Genomic Data Science Wrap-Up (1:53)1мин
Reading1 материал для самостоятельного изучения
Post Course Survey10мин
Quiz1 практическое упражнение
Module 4 Quiz10мин
4.1
Direction Signs

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Briefcase

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Money

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Лучшие рецензии

автор: ZMJun 28th 2018

The professor is really enthusiasm, so I was really impreesed by him. And his teaching is brief, and I can learn key points through the lectures. Great course!

автор: LRMay 23rd 2016

I have really enjoyed the course and I have learnt different concepts relevant for my current study.\n\nYurany

Преподаватель

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

О Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

О специализации ''Genomic Data Science'

This specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, Python, R, Bioconductor, and Galaxy. The sequence is a stand alone introduction to genomic data science or a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics. To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit....
Genomic Data Science

Часто задаваемые вопросы

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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