Acerca de este Curso
4.1
138 calificaciones
26 revisiones
Programa Especializado
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100% online

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Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Hours to complete

Aprox. 18 horas para completar

Sugerido: 6 hours/week...
Available languages

Inglés (English)

Subtítulos: Inglés (English)...

Habilidades que obtendrás

StatisticsData AnalysisR ProgrammingBiostatistics
Programa Especializado
100% online

100% online

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Hours to complete

Aprox. 18 horas para completar

Sugerido: 6 hours/week...
Available languages

Inglés (English)

Subtítulos: Inglés (English)...

Programa - Qué aprenderás en este curso

Semana
1
Hours to complete
3 horas para completar

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 videos (Total: 129 min), 3 readings, 1 quiz
Video21 videos
What is Statistics?2m
Finding Statistics You Can Trust (4:44)4m
Getting Help (3:44)3m
What is Data? (4:28)4m
Representing Data (5:23)5m
Module 1 Overview (1:07)1m
Reproducible Research (3:42)3m
Achieving Reproducible Research (5:02)5m
R Markdown (6:26)6m
The Three Tables in Genomics (2:10)2m
The Three Tables in Genomics (in R) (3:46)3m
Experimental Design: Variability, Replication, and Power (14:17)14m
Experimental Design: Confounding and Randomization (9:26)9m
Exploratory Analysis (9:21)9m
Exploratory Analysis in R Part I (7:22)7m
Exploratory Analysis in R Part II (10:07)10m
Exploratory Analysis in R Part III (7:26)7m
Data Transforms (7:31)7m
Clustering (8:43)8m
Clustering in R (9:09)9m
Reading3 lecturas
Syllabus10m
Pre Course Survey10m
Introduction and Materials10m
Quiz1 ejercicios de práctica
Module 1 Quiz20m
Semana
2
Hours to complete
2 horas para completar

Module 2

This week we will cover preprocessing, linear modeling, and batch effects....
Reading
14 videos (Total: 97 min), 1 quiz
Video14 videos
Dimension Reduction (12:13)12m
Dimension Reduction (in R) (8:48)8m
Pre-processing and Normalization (11:26)11m
Quantile Normalization (in R) (4:49)4m
The Linear Model (6:50)6m
Linear Models with Categorical Covariates (4:08)4m
Adjusting for Covariates (4:16)4m
Linear Regression in R (13:03)13m
Many Regressions at Once (3:50)3m
Many Regressions in R (7:21)7m
Batch Effects and Confounders (7:11)7m
Batch Effects in R: Part A (8:18)8m
Batch Effects in R: Part B (3:50)3m
Quiz1 ejercicios de práctica
Module 2 Quiz20m
Semana
3
Hours to complete
2 horas para completar

Module 3

This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing....
Reading
15 videos (Total: 86 min), 1 quiz
Video15 videos
Logistic Regression (7:03)7m
Regression for Counts (5:02)5m
GLMs in R (9:28)9m
Inference (4:18)4m
Null and Alternative Hypotheses (4:45)4m
Calculating Statistics (5:11)5m
Comparing Models (7:08)7m
Calculating Statistics in R9m
Permutation (3:26)3m
Permutation in R (3:33)3m
P-values (6:04)6m
Multiple Testing (8:25)8m
P-values and Multiple Testing in R: Part A (5:58)5m
P-values and Multiple Testing in R: Part B (4:23)4m
Quiz1 ejercicios de práctica
Module 3 Quiz20m
Semana
4
Hours to complete
2 horas para completar

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 videos (Total: 74 min), 1 reading, 1 quiz
Video14 videos
Gene Set Enrichment (4:19)4m
More Enrichment (3:59)3m
Gene Set Analysis in R (7:43)7m
The Process for RNA-seq (3:59)3m
The Process for Chip-Seq (5:25)5m
The Process for DNA Methylation (5:03)5m
The Process for GWAS/WGS (6:12)6m
Combining Data Types (eQTL) (6:04)6m
eQTL in R (10:36)10m
Researcher Degrees of Freedom (5:49)5m
Inference vs. Prediction (8:52)8m
Knowing When to Get Help (2:31)2m
Statistics for Genomic Data Science Wrap-Up (1:53)1m
Reading1 lecturas
Post Course Survey10m
Quiz1 ejercicios de práctica
Module 4 Quiz10m
4.1
Career direction

25%

comenzó una nueva carrera después de completar estos cursos
Career Benefit

83%

consiguió un beneficio tangible en su carrera profesional gracias a este curso
Career promotion

25%

consiguió un aumento de sueldo o ascenso

Principales revisiones

por 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!

por LRMay 23rd 2016

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

Instructores

Avatar

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Acerca de 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....

Acerca del programa especializado 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

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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