Explore
For Enterprise
Join for Free
Log In

Navegar
Pesquisar
For Enterprise
Entrar
Inscreva-se gratuitamente

Module 1 Overview (1:07)

Loading...

Estatística para Análise de Dados Genômicos

Universidade Johns Hopkins

4.1 (193 classificações) | 17K alunos inscritos

Curso 7 de 8 no Análise de Dados GenômicosAnálise Genômica Programa de cursos integrados

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.

Visualizar o programa do curso

Habilidades que você aprenderá

Statistics, Data Analysis, R Programming, Biostatistics

Avaliações

4.1 (193 classificações)

5 stars
99 ratings
4 stars
53 ratings
3 stars
20 ratings
2 stars
8 ratings
1 star
13 ratings

LR

May 23, 2016

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

TK

Mar 25, 2019

Very good course and useful understanding statistical aspects of data.

Na lição

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.

Module 1 Overview (1:07)1:07

Reproducible Research (3:42)3:42

Achieving Reproducible Research (5:02)5:02

R Markdown (6:26)6:26

The Three Tables in Genomics (2:10)2:10

The Three Tables in Genomics (in R) (3:46)3:46

Experimental Design: Variability, Replication, and Power (14:17)14:17

Experimental Design: Confounding and Randomization (9:26)9:26

Exploratory Analysis (9:21)9:21

Exploratory Analysis in R Part I (7:22)7:22

Exploratory Analysis in R Part II (10:07)10:07

Exploratory Analysis in R Part III (7:26)7:26

Data Transforms (7:31)7:31

Clustering (8:43)8:43

Clustering in R (9:09)9:09

Ministrado por

Jeff Leek, PhD
Associate Professor, Biostatistics

Transcrição

Welcome to week one of Statistics for Genomic Data Science. I just want to give you a quick overview of what we're going to be learning about this week. So this week we're going to be talking about two main things. First, we're going to be talking about background, both about Statistics and about Genomics, as well as installing all of the relevant software. For example, the Bioconductor packages and showing you how to install Bioconductor packages and so forth. This is basically just sort of our ramp up week in that sense and the sense that we're going to sort of give you all the background information so that you can kind of tackle the rest of the weeks of the class. Then the next thing that we're going to do is we're going to talk a little bit about background of Statistics. So we're going to talk a little bit about what are the main and key concepts in Statistics, and whether who's the target that we're shooting for in the rest of the class. And then finally we're going to talk a little bit about exploratory data analysis this week. And so we're going to talk about what kind of plots you can make. What kind of summaries of data that you can make. And how can you sort of interact with data at a very raw level that gives you some intuition about what's going on. I think this is one of the funnest parts of Statistics is exploratory data analysis. And so we're going to lead off with one of the best parts

Explore nosso catálogo

Registre-se gratuitamente e obtenha recomendações, atualizações e ofertas personalizadas.

O Coursera proporciona acesso universal à melhor educação do mundo fazendo parcerias com as melhores universidades e organizações para oferecer cursos on-line.

© 2019 Coursera Inc. Todos os direitos reservados.

Baixar no Google Play

Coursera
Sobre
Liderança
Carreiras
Lista de cursos
Certificados
Certificados MasterTrack™
Notas
For Enterprise
For Government
For Campus

Comunidade
Learners
Partners
Developers
Beta Testers
Translators

Conectar
Blog
Facebook
LinkedIn
Twitter
Instagram
YouTube
Tech Blog

Mais
Termos
Privacidade
Ajuda
Acessibilidade
Imprensa
Contato
Diretório
Afiliados