課程大綱： 基因組數據科學頂點項目培訓
IntroductionIn 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.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.
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.Alignment
Once you have understood the problem,
the next step is to obtain the raw data so that you can perform your analysis.
QC the AlignmentNow you have aligned the data, the next step is to do some quality control to make sure that the data are in good shape.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.Exploratory Analysis
After summarizing your genomic data the next step is to load the data into R for analysis with Bioconductor.Statistical Analysis
The next step is to perform a statistical analysis to detect genes that are differentially expressed.
Gene Set AnalysisIn task 6, we have identified genes differentially expressed between fetal and adult brain.
Now we will examine these results in a wider context.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.
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