Lecture

Learning objectives

By the end of this lesson, we should become more comfortable with interpreting our clusters identified from our analysis pipeline thus far using differential gene expression. We will also perform differential expression analysis, learn how to create different data visualizations to summarize our analysis, and use these visualizations and summaries to evaluate our analysis pipeline.

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Hands-on Component

Our in-class hands-on component will analyze our spatial transcriptomics dataset to identify differentially expressed genes and make data visualizations.

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Class Notes

Prof. Fan’s notes from class: genomic-data-visualization-Lesson_7.pptx (click to download)

Prof. Fan’s code from class: code-lesson-7.R (click to download)

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Homework Assignment

Put everything you’ve learned together: perform clustering analysis, differential expression, visualize results in reduced dimensional space and physical space, interpret your cluster identified.

Additional details: genomic-data-visualization-HW_4.pptx (click to download)