Lecture 2

2.0 Lesson learning objectives

By the end of this lesson, we should understand what is spatially resolved transcriptomic data, how the data is generated, and how we can begin visualizing and interacting with the data.

2.1 Why spatially resolved transcriptomics?

2.2 Low-throughput approaches for spatially resolved transcriptomic profiling

smFISH

microdissection (to be covered at later date)

2.3 High-throughput approaches for spatially resolved transcriptomic profiling

Spatially resolved highly multiplxed transcriptomic imaging with MERFISH

MERFISH is an imaging method capable of simultaneously measuring the copy number and spatial distribution of hundreds to thousands of RNA species in fixed cells. This technique was introduced in the paper Chen et al. Spatially resolved, highly multiplexed RNA profiling in single cells. Science (2015)

Spatially resolved transcriptomic sequencing with Visium (to be covered at later date)

Visium is a commercial platform that uses glass slides with arrayed oligonucleotides containing positional barcodes to generate cDNA libraries with positional information for RNA sequencing. The technique was introduced in the paper Stahl et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science (2016) and later licensed to 10X Genomics for commercialization.

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Hands-on component 2

Our in-class hands-on component will involve forming teams, downloading, and beginning to analyze spatial transcriptomics data.

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Class Lesson Notes 2

Prof. Fan’s whiteboard notes from class: (for some reason it didn’t save; please refer to recording instead)

Prof. Fan’s code from class: code-01-27-2023.R (click to download)

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Homework Assignment 2

Make a new data visualization of your spatial transcriptomics dataset using ggplot (do not make the same visualizations that were made in class). Write a description of what you did using vocabulary terms from Lesson 1. See slides for more details on what is expected and how to submit your homework.

genomic-data-visualization-HW_1.pptx (click to download)

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