Homework 1

1. What data types are you visualizing?

I am visualizing quantitative data of the expression of CD3D and PRF1 genes (2 quantitative variables) for each cell. Also, I am showing spatial data regarding the x,y centroid positions for each cell.

2. What data encodings (geometric primitives and visual channels) are you using to visualize these data types?

I am using the geometric primitive of points to represent each cell.
To encode expression counts of CD3D gene I am using the visual channel of color, and size for PRF1 gene.
For variables “aligned_x” and “aligned_y” I am using the visual channel of position along the x axis and y axis, respectively. That allows me to take advantage of the spatial location and compare it with any tissue staining I might have (e.g. H&E).

3. What about the data are you trying to make salient through this data visualization?

My data visualization seeks to make more salient the spatial location of T cells within the tissue slide, which are immune cells positive for CD3D expression. On top of that, I want to highlight cytotoxic cells bearing a high PRF1 expression.

4. What Gestalt principles or knowledge about perceptiveness of visual encodings are you using to accomplish this?

My plot is using the similarity principle. Cells that have a similar CD3D expression have a similar color. In the same way, all cells with high levels of PRF1 will be bigger than cells with lower expression levels.

5. Code

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# Import libraries
library(ggplot2)
library(tidyverse)

# Read data
file <- '/Users/kmlanderos/Documents/Johns_Hopkins/Spring_2025/Genomic_Data_Visualization/genomic-data-visualization-2025/data/pikachu.csv.gz'
data <- read.csv(file, row.names=1)

# Number of cells
nrow(data)
# Number of genes
ncol(data[,6:ncol(data)])

# Create plot
data %>% arrange(CD3D) %>% mutate(cell_area=log2(cell_area), CD8_CD4_ratio=CD8A/CD4) %>%
  ggplot(aes(x=aligned_x, y=aligned_y, col=CD3D)) + 
    scale_colour_gradient(low = 'lightgrey', high='#2810fe') + 
    #geom_point(size = 1) +
    geom_point(aes(size = PRF1)) + 
    scale_size_continuous(range = c(0.2, 2)) + 
    theme_minimal() +
    labs(
      title = "Scatter plot highlighting spatial location of T cells and cytotoxic cells",
      x = "X coordinate",
      y = "Y coordinate",
      size = "PRF1 Expression",
      color = "CD3D Expression",
      shape = "CD4+/CD8+ T cell"
    )