Welcome

Welcome to the Course Website for EN.580.428 Genomic Data Visualization!

As the primary mode through which analysts and audience members alike consume data, data visualization remains an important hypothesis generating and analytical technique in data-driven research to facilitate new discoveries. However, if done poorly, data visualization can also mislead, bias, and slow down progress. This hands-on course will cover the principles of perception and cognition relevant for data visualization and apply these principles to genomic data, including large-scale single-cell and spatially-resolved omics datasets, using the R statistical programming language. Students will be expected to complete class readings, create weekly data visualizations as homework assignments, and make a major class presentation.

Course Information

Course Staff: Prof. Jean Fan and Rafael dos Santos Peixoto
Lectures: 8:00am-9:50am Monday, Wednesday, and Friday. See Canvas for location details.
Office Hours: 10:00am-10:50am Monday, Wednesday, and Friday. See Canvas for location details.

Course Details
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All Visualizations

Comparing the effect of tSNE on varying number of PCs:KRT7 expression

I am visualizing the effect of performing non-linear dimensionality reduction (TSNE) on varying number of PCs. The gene expression was normalized (by total gene expression for each cell) prior to...

Centroid positions, cell and nucleus areas of each cell

What genes (or other cell features such as area or total genes detected) are driving my reduced dimensional components?

Varying the number of principal components used to perform non-linear dimensionality reduction on barcode-based sequencing data

Description of Data Visualization Three graphs are used to illustrate the impact of increasing the number of principal components used for non-linear dimensionality reduction. Points are used as a geometric...

Effect of Introducing Principle Components on Non-linear Dimensionality Reduction

What data types are you visualizing? In the multi-panel plot, I am visualizing spatial and quantitative data with diffrerent projection approaches. The visualization contains spatial data of each cell’s position...

Normalization of gene expression prior to dimensionality reduction for Spatial Transcriptomic dataset

What happens if I do or not not normalize and/or transform the gene expression data (e.g. log and/or scale) prior to dimensionality reduction?

Effect of Normalization on Dimensionality Reduction

Description of the data visualization

Varying non-linear dimensionality reduction on PCs

###I explored the question: If I perform non-linear dimensionality reduction on PCs, what happens when I vary how many PCs should I use?​

Comparison of Gene Influence on PC1 in Raw and Cell Area-Normalized Data

Write a description describing your data visualization using vocabulary terms from Lesson 1. What data types are you visualizing? What data encodings (geometric primitives and visual channels) are you using...

Comparison between normalized vs not normalized dimensionality reduction on IGKC expression

What happens if I do or not not normalize and/or transform the gene expression data (e.g. log and/or scale) prior to dimensionality reduction? I compared dimensionality reduction on normalized vs...

Exploring Gene Expression Effects on Linear and Nonlinear Dimensionality Reduction

What’s the difference if I perform linear or nonlinear dimensionality reduction to visualize my cells in 2D? When visualizing the cells in 2D, nonlinear dimensionality reduction showed a more well-defined...

Comparison of Linear and Nonliner Dimensionality Reduction

What’s the difference if I perform linear or nonlinear dimensionality reduction to visualize my cells in 2D? Linear dimensionality reductions, such as principle component analysis, works best with data that...

Classmate Visualization: Visualizing Locations of Different Gene Expressions

Whose code are you applying? https://jef.works/genomic-data-visualization-2024/blog/2024/01/29/dvelazq5/