Merge pull request #44 from tsinha15/main

tsinha5 HW1

_posts/2024-01-27-tsinha5.md

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+---
+layout: post
+title:  "Heatmap of the ACAP3 gene"
+author: Tanishk Sinha
+jhed: tsinha5
+categories: [ HW1 ]
+image: homework/hw1/HW1_tsinha5.png
+featured: false
+---
+
+### What data types are you visualizing?
+I am visualizing quantitative data of the expression count of the ACAP3 gene within a single cell and spatial data regarding the x,y position for each bead within which the RNA count is measured.
+
+### 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 bead. To encode expression count of the ACAP3 gene, I am using the visual channel of color hue from red to blue. To encode the spatial position of the bead, I am positioning the points along the x (600 to 1100) and y (800 to 1150) axis. Color hue from red to blue is also being used in the legend to encode expression count of the ACAP3 gene.
+
+### What about the data are you trying to make salient through this data visualization? 
+My data visualization seeks to make more salient the relationship between the density of ACAP3 gene expression count and the position within a cell. 
+
+### What Gestalt principles or knowledge about perceptiveness of visual encodings are you using to accomplish this?
+The principle of similarity is used to identify areas of similar ACAP3 gene expression density.
+
+```{r}
+data2 <- read.csv('eevee.csv.gz', row.names = 1)
+data <- data2
+library(ggplot2)
+
+ggplot(data, aes(x = aligned_x, y = aligned_y)) + 
+  #making the tiles, reference source: https://github.com/rstudio/cheatsheets/blob/main/data-visualization.pdf
+  geom_tile(aes(fill = ACAP3, width = 14, height = 14)) + 
+  #square tiles, reference source: https://r-charts.com/correlation/heat-map-ggplot2/
+  coord_fixed() + 
+  #color gradient, reference source: https://r-charts.com/correlation/heat-map-ggplot2/
+  scale_fill_gradient(low = 'blue', high = 'red')