#Import file of Upregulated Genes
Comparison_of_DEG_by_Significance_Up <- read_excel("Comparison of DEG by Significance Up.xlsx", col_types = c("text", "numeric", "numeric", "numeric", "numeric", "numeric", "numeric"))
print(Comparison_of_DEG_by_Significance_Up)
## # A tibble: 58 × 7
## Upregulated_Genes Overall Original_Author Colon Author_HCE Blood_Vessel
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 BIRC3 0 20 19 17 0
## 2 C11orf96 0 0 0 0 0
## 3 CCL2 20 19 9 11 16
## 4 CCL20 7 18 0 0 0
## 5 CEBPD 6 0 0 0 0
## 6 CSF1 13 0 10 0 0
## 7 CSF2 1 17 0 0 0
## 8 CSF3 0 16 0 0 0
## 9 CXCL1 19 15 4 0 19
## 10 CXCL10 0 14 0 0 0
## # ℹ 48 more rows
## # ℹ 1 more variable: Author_HCAE <dbl>
## Melt table into long version
comparison_up_long <- pivot_longer(data = Comparison_of_DEG_by_Significance_Up, cols = -c(Upregulated_Genes), names_to = "Study", values_to = "Significance")
comparison_up_long
## # A tibble: 348 × 3
## Upregulated_Genes Study Significance
## <chr> <chr> <dbl>
## 1 BIRC3 Overall 0
## 2 BIRC3 Original_Author 20
## 3 BIRC3 Colon 19
## 4 BIRC3 Author_HCE 17
## 5 BIRC3 Blood_Vessel 0
## 6 BIRC3 Author_HCAE 0
## 7 C11orf96 Overall 0
## 8 C11orf96 Original_Author 0
## 9 C11orf96 Colon 0
## 10 C11orf96 Author_HCE 0
## # ℹ 338 more rows
## Import Downregulated Genes
Comparison_of_DEG_by_Significance_Down <- read_excel("Comparison of DEG by Significance Down.xlsx", col_types = c("text", "numeric", "numeric", "numeric", "numeric", "numeric", "numeric"))
print(Comparison_of_DEG_by_Significance_Down)
## # A tibble: 76 × 7
## Downregulated_Genes Overall Original_Author Colon Author_HCE Blood_Vessel
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 ABCA8 0 0 0 0 19
## 2 AP5S1 0 20 0 0 0
## 3 ARID5B 0 0 13 0 0
## 4 ARFGAP2 0 19 0 0 0
## 5 ASCL2 8 0 18 16 0
## 6 ASNS 0 18 0 0 0
## 7 BMI1 0 17 0 0 0
## 8 BOC 0 0 2 0 0
## 9 BRCA2 0 0 0 0 0
## 10 BRD8 0 0 0 0 9
## # ℹ 66 more rows
## # ℹ 1 more variable: Author_HCAE <dbl>
## Melt table into long version
comparison_down_long <- pivot_longer(data = Comparison_of_DEG_by_Significance_Down, cols = -c(Downregulated_Genes), names_to = "Studies", values_to = "Significance_Down")
comparison_down_long
## # A tibble: 456 × 3
## Downregulated_Genes Studies Significance_Down
## <chr> <chr> <dbl>
## 1 ABCA8 Overall 0
## 2 ABCA8 Original_Author 0
## 3 ABCA8 Colon 0
## 4 ABCA8 Author_HCE 0
## 5 ABCA8 Blood_Vessel 19
## 6 ABCA8 Author_HCAE 0
## 7 AP5S1 Overall 0
## 8 AP5S1 Original_Author 20
## 9 AP5S1 Colon 0
## 10 AP5S1 Author_HCE 0
## # ℹ 446 more rows
## Plot Compiled Downregulated Data
downregulated_heatmap <- ggplot (data = comparison_down_long, mapping = aes(x = Downregulated_Genes, y = Studies, fill = Significance_Down)) + geom_tile() + xlab(label = "Genes")
downregulated_heatmap + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) + scale_fill_gradient(low = "#e5ebf0",
high = "darkred",
limits = c(0, 20))
DEG_Across_Cell_Types <- read_excel("DEG Across Cell Types.xlsx")
DEG_Across_Cell_Types
## # A tibble: 30 × 4
## Cell_Type Gene_Name Fold_Change_HCE Fold_Change_HCAE
## <chr> <chr> <dbl> <dbl>
## 1 Colon C9orf152 -2.03 0
## 2 Colon TNFRSF19 -1.77 0
## 3 Colon PATZ1 -1.46 0
## 4 Blood_Vessel DOP1A 0 -2.03
## 5 Blood_Vessel ABCA8 0 -2.06
## 6 Blood_Vessel PPFIBP2 0 -1.61
## 7 Blood_Vessel CNTRL 0 -2.45
## 8 Blood_Vessel KLF2 0 -1.45
## 9 Colon KCNE3 -1.57 0
## 10 Colon ARID5B -1.42 0
## # ℹ 20 more rows
require("ggrepel")
## Loading required package: ggrepel
ggplot(DEG_Across_Cell_Types) +
geom_point(aes(x = Fold_Change_HCE,
y = Fold_Change_HCAE,
color = Cell_Type)) +
geom_text_repel(aes(x = Fold_Change_HCE,
y = Fold_Change_HCAE,
label = Gene_Name))
