Genomic Data Science Capstone

Methode

Genomic Data Science Capstone

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Beschreibung

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  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: In this culminating project, you will deploy the tools and techniques that you've mastered over the course of the specialization. You'll work with a real data set to perform analyses and prepare a report of your findings.

Created by:  Johns Hopkins University
  • Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Kasper Daniel Hansen, PhD, Assistant Professor, Biostatistics and Genetic Medicine

    Bloomberg School of Public Health
Basic Info Course 8 of 8 in the Genomic Data Science Specialization Commitment 8 weeks of study, 2-4 hours/week Language English How To Pass Pa…

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Frequently asked questions

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: In this culminating project, you will deploy the tools and techniques that you've mastered over the course of the specialization. You'll work with a real data set to perform analyses and prepare a report of your findings.

Created by:  Johns Hopkins University
  • Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health
  • Taught by:  Kasper Daniel Hansen, PhD, Assistant Professor, Biostatistics and Genetic Medicine

    Bloomberg School of Public Health
Basic Info Course 8 of 8 in the Genomic Data Science Specialization Commitment 8 weeks of study, 2-4 hours/week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.6 stars Average User Rating 4.6See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Syllabus


WEEK 1


Introduction
In this first week, we'll introduce the project and get you oriented to the tasks that you'll be performing over the next several weeks.


1 video, 6 readings expand


  1. Video: Introduction to the Capstone - Kasper Hansen
  2. Reading: Welcome
  3. Reading: The big question
  4. Reading: What you will be doing in this capstone project
  5. Reading: Passing the Capstone
  6. Reading: Why re-analysis?
  7. Reading: Why is this so hard?


WEEK 2


Introduction to the Dataset - Andrew Jaffe



This week, we'll really dig into the dataset by providing an introduction from Andrew Jaffe, the lead scientist on the analysis. You should also be looking ahead to Task 2, which is due in Week 4; the alignment will take a long time to perform, so you should start early.


1 video, 3 readings expand


  1. Video: The Dataset - Andrew Jaffe
  2. Reading: Phenotype information
  3. Reading: Getting the data from SRA
  4. Reading: Which samples to use


WEEK 3


Understand the Problem



The purpose of genomic data science is to answer fundamental questions in biology. Before starting on the data analysis process, the first step is always to understand the scientific question you are trying to answer. Don't forget to stay on top of the alignment task due in Week 4; it will take a long time to accomplish and shouldn't be put off.


1 video, 1 reading expand


  1. Reading: Task 1 Instructions
  2. Video: The Results - Andrew Jaffe
  3. Discussion Prompt: What did you find challenging about task 1?

Graded: Understand the problem

WEEK 4


Alignment
Once you have understood the problem, the next step is to obtain the raw data so that you can perform your analysis.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 2?

Graded: Alignment

WEEK 5


QC the Alignment
Now you have aligned the data, the next step is to do some quality control to make sure that the data are in good shape.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 3?

Graded: QC the Alignment

WEEK 6


Get Feature Counts
Now that you have performed alignment and quality control, the next step is to calculate the abundance of every gene in every sample.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 4?

Graded: Get Feature Counts

WEEK 7


Exploratory Analysis
After summarizing your genomic data the next step is to load the data into R for analysis with Bioconductor.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 5?

Graded: Exploratory Analysis

WEEK 8


Statistical Analysis
The next step is to perform a statistical analysis to detect genes that are differentially expressed.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 6?

Graded: Statistical Analysis

WEEK 9


Gene Set Analysis
In task 6, we have identified genes differentially expressed between fetal and adult brain. Now we will examine these results in a wider context.


3 items expand


  1. Discussion Prompt: What did you find challenging about task 7?
  2. Peer Review: Optional Peer Review of Your Report Draft

Graded: Gene Set Analysis

WEEK 10


Describe Your Analysis
The next step is to document your work. One of the major issues in genomic data science is that there are so many steps in the process. If these steps are not documented well the result can be major problems.


2 items expand


  1. Discussion Prompt: What did you find challenging about task 8?

Graded: Describe Your Analysis

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