Lecture 6

6.0 Lesson learning objectives

By the end of this lesson, we should understand what is kmeans clustering and how to apply it to our spatial transcriptomic datasets.

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Hands-on component 6

Our in-class hands-on component will analyzing either the MERFISH or Visium dataset to create a data visualization using kmeans clustering.

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Class Lesson Notes 6

Prof. Fan’s whiteboard notes from class: genomic-data-visualization-classnotes-20220207.pdf (click to download)

Prof. Fan’s code from class: inclass-plotting-20220207.R (click to download)

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Homework Assignment 6

You will be given a data visualization made using the data analysis techniques you have learned about in class. This data visualization is a figure from a scientific publication. The authors have described particular points that they have tried to make more salient using these data visualizations.

Your homework is to write a description of these data visualizations using vocabulary you have learned about in Lesson 1. Include in your description the data type that is being visualized, the geometric primitives and visual channels used, and whether you think the authors were effective in their data visualization. Include also a description of how you could change this data visualization to improve saliency.

See slides for more details on what is expected and how to submit your homework.

genomic-data-visualization-HW_2.pptx (click to download)

Make a pull request to submit your homework (due Wednesday Midnight).

Please also install the gridExtra package by running in R the command install.packages('gridExtra') for the hands-on component of the next class.

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