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 Kalen Clifton
Office Hours: 10:00am-10:50am Monday, Wednesday, and Friday. See Slack for location details.
Lectures: 8:00am-9:50am Monday, Wednesday, and Friday. See Slack for location details.
Course Details
☞ see Course tabFeatured Visualizations
Cell Type Exploration of Charmander Data Set
The cluster appears to be endothelial cells that make up adipose tissue. When looking at the Wilcox vs log2fc graph three of most significantly upregulated...
Identification of a Cluster Associated with CD8+ T cells
Description of my multi-panel plot Here, I identified a cluster that seems to be CD8+ T cells. In order to generate the plot above, I...
Homework 5
Description
Validation of cell type clustering via differential gene expression
The purpose of this visualization to present the usage of differential gene expression to validate cell type identification in k-means and tsne analysis of the...
Running tSNE analysis on genes or PCs
What data types are you visualizing? In this multi-panel plot, I am visualizing various quantitative and categorical data. For the PCA plot on the upper...
AQP1 Expression for Contrasting Principle Component Numbers
What data types are you visualizing? I am using categorical data (zero and nonzero expression) as well as quantitative (color gradient of expression).
Comparison of Dimensionality Reduction Methods for Representation of Clustered Data
What data are you visualizing
The effect of Count Per Million normalization on Dimensionality Reduction
What data types are you visualizing? I am visualizing quantitative data of cells’ position on tSNE embedded 2-dimensional space. I am also visualizing the total...
Cells Clustered By Gene Expression
What data are you visualizing
Comparative detection of KRT7 and PTPRC gene expression
What data types are you visualizing? I am visualizing categorical data of the comparative gene expression detection of two genes KRT7 and PTPRC. There are...
Spatial position of cells with low gene count
What data types are you visualizing? I am visualizing the categorical data of the presence of 3 or fewer genes in a cell together with...
Comparing the relationship between Growth Factor Receptors Expression and Cell Area
What data types are you visualizing? I am visualizing quantitative data of the expression count of the EGFR, PDGFRA and PDGFRB genes for each cell,...
All Visualizations
Cell type identification based on clustering and gene expression on the Visium breast cancer dataset
Given the differential gene expression analysis, the cell type equivalent to cluster 1 in the data file is most likely a macrophage. Having identified the overexpressed genes in this cluster...
Identification of two Cell Clusters
In my plots, I am looking at cell clusters 1 and 8. These clusters separate strongly from the other cells along PC1 and remain close together on t-SNE projections. In...
Cell Type Exploration of Charmander Data Set
The cluster appears to be endothelial cells that make up adipose tissue. When looking at the Wilcox vs log2fc graph three of most significantly upregulated genes are CAV1, VWF, and...
Differentially expressed genes and cell-type annotation for cluster 2
Cell-type annotation For this data visualization, we selected cluster 2 as it presented an interesting pattern. Then, by performing kmeans clustering and differential analysis on the normalized data, we noticed...
Multi-panel data visualization of k-means clustering results and gene expression
The data visualization chooses cluster 3 to be analyzed. It then identifies gene that are differentially expressed in that cluster compared to all the other clusters in the dataset. The...
Description of HW5
In order to determine cell type from cell cluster, I aimed to find particular genes which are both highly specific to one type of breast cell and also present in...
Identification of a Cluster Associated with CD8+ T cells
Description of my multi-panel plot Here, I identified a cluster that seems to be CD8+ T cells. In order to generate the plot above, I normalized the raw gene expression...
Determining Cell Type with Kmeans Approach
I used kmeans clustering to identify different cell types by looking at clusters in my data. I preproceessed my data by normalizing by total gene count and putting everything on...
