Update manuscript figures per review (#72)

* update manuscript figure per review

* add figure 4 to main README

3.figures/main_figure_4/scripts/2.generate_image_montage.r

@@ -96,7 +96,7 @@ list_of_images <- list(
 width <- 2.5
 height <- 2.5
 
-text_size <- 8
+text_size <- 10
 
 options(repr.plot.width = width, repr.plot.height = height)
 
@@ -194,17 +194,17 @@ options(repr.plot.width = width, repr.plot.height = height)
 # ggplot of just text
 radial_feat_text <- (
     ggplot()
-    + geom_text(aes(x = 0.5, y = 0.5, label = "Cytoplasm_RadialDistribution_FracAtD_RFP_4of4"), size = text_size) 
+    + geom_text(aes(x = 0.5, y = 0.5, label = "CellProfiler feature:\nCytoplasm_RadialDistribution_FracAtD_RFP_4of4"), size = text_size) 
     + theme_void()
 )
 int_feat_text <- (
     ggplot()
-    + geom_text(aes(x = 0.5, y = 0.5, label = "Cytoplasm_Intensity_MeanIntensityEdge_GFP"), size = text_size) 
+    + geom_text(aes(x = 0.5, y = 0.5, label = "CellProfiler feature:\nCytoplasm_Intensity_MeanIntensityEdge_GFP"), size = text_size) 
     + theme_void()
 )
 corr_feat_text <- (
     ggplot()
-    + geom_text(aes(x = 0.5, y = 0.5, label = "Cells_Correlation_Correlation_DAPI_GFP"), size = text_size) 
+    + geom_text(aes(x = 0.5, y = 0.5, label = "CellProfiler feature:\nCells_Correlation_Correlation_DAPI_GFP"), size = text_size) 
     + theme_void()
 )
 
@@ -233,8 +233,8 @@ options(repr.plot.width = width, repr.plot.height = height)
 radial_patch_text
 
 # Create montage
-width <- 12.5
-height <- 8
+width <- 17.5
+height <- 11
 
 options(repr.plot.width = width, repr.plot.height = height)
 
@@ -259,8 +259,8 @@ ggsave(
 )
 
 # Create montage
-width <- 12.5
-height <- 8
+width <- 17.5
+height <- 11
 
 options(repr.plot.width = width, repr.plot.height = height)
 
@@ -285,8 +285,8 @@ ggsave(
 )
 
 # Create montage
-width <- 12.5
-height <- 8
+width <- 17.5
+height <- 11
 
 options(repr.plot.width = width, repr.plot.height = height)
 
@@ -309,3 +309,5 @@ ggsave(
     ),
     corr_feat_plot, width = width, height = height, dpi = 600
 )
+
+

3.figures/main_figure_4/scripts/3.main_figure_4.r

@@ -310,8 +310,8 @@ radial_montage <- ggplot() +
 radial_montage
 
 bottom_montage <- (
-   free(corr_montage) | 
-   radial_montage
+   free(radial_montage) | 
+   corr_montage
 ) + plot_layout(widths = c(1,1.25))
 
 bottom_montage

3.figures/supp_figure_1/scripts/SuppFigure1_splitbyplate.r

@@ -2,7 +2,6 @@ suppressPackageStartupMessages(library(dplyr))
 suppressPackageStartupMessages(library(ggplot2))
 suppressPackageStartupMessages(library(grid))
 suppressPackageStartupMessages(library(patchwork))
-suppressPackageStartupMessages(library(platetools))
 
 figure_dir <- "../figures/supplementary"
 output_supp_figure_1 <- file.path(figure_dir, "supp_figure_1_splitbyplate.png")
@@ -17,6 +16,12 @@ UMAP_results_file <- file.path(UMAP_results_dir, "UMAP_concat_model_plates_sc_fe
 
 UMAP_results_df <- readr::read_tsv(UMAP_results_file)
 
+UMAP_results_df <- UMAP_results_df %>%
+  mutate(Metadata_Plate = recode(Metadata_Plate,
+                        "Plate_3" = "Plate A",
+                        "Plate_3_prime" = "Plate B",
+                        "Plate_5" = "Plate C"))
+
 dim(UMAP_results_df)
 head(UMAP_results_df)
 
@@ -106,6 +111,19 @@ corr_results_dir <- file.path(
 corr_results_file <- file.path(corr_results_dir, "well_agg_plate_genotype_correlations.parquet")
 corr_results_df <- arrow::read_parquet(corr_results_file)
 
+# Rename plates in both group columns
+corr_results_df <- corr_results_df %>%
+  mutate(
+    Metadata_Plate__group0 = recode(Metadata_Plate__group0,
+                                    "Plate_3" = "Plate A",
+                                    "Plate_3_prime" = "Plate B",
+                                    "Plate_5" = "Plate C"),
+    Metadata_Plate__group1 = recode(Metadata_Plate__group1,
+                                    "Plate_3" = "Plate A",
+                                    "Plate_3_prime" = "Plate B",
+                                    "Plate_5" = "Plate C")
+  )
+
 # Filter rows where Metadata_Plate__group0 matches Metadata_Plate__group1
 filtered_df <- corr_results_df %>%
     filter(Metadata_Plate__group0 == Metadata_Plate__group1)

3.figures/supp_figure_2/README.md

@@ -1,8 +1,8 @@
-# Creating supplemental figure 2 - Image quality control distributions
+# Creating supplemental figure 2 - Plate maps
 
 To generate the second supplemental figure of the manuscript, there is one step to follow:
 
-1. [SuppFigure2_qualitycontrol.ipynb](./SuppFigure2_qualitycontrol.ipynb): Generate distribution plots for blur and saturation metrics across plate, and patch the plots together to make one figure.
+1. [SuppFigure2_platemaps.ipynb](./SuppFigure2_platemaps.ipynb): Generate platemap layout figures per plate.
 
 All steps can be ran with the bash script using the command below:
 

3.figures/supp_figure_2/scripts/SuppFigure2_platemaps.r

@@ -0,0 +1,82 @@
+suppressPackageStartupMessages(library(dplyr))
+suppressPackageStartupMessages(library(ggplot2))
+suppressPackageStartupMessages(library(platetools))
+suppressPackageStartupMessages(library(patchwork))
+
+figure_dir <- "../figures/supplementary"
+output_supp_figure_2 <- file.path(figure_dir, "supp_figure_2_platemaps.png")
+
+# Path to platemaps
+platemap_dir <- file.path(
+    "../../../nf1_cellpainting_data/0.download_data/metadata"
+)
+
+# Load data
+plate_A_B_file <- file.path(platemap_dir, "platemap_NF1_plate3.csv")
+
+plate_A_B_df <- readr::read_csv(plate_A_B_file)
+
+# Remove rows where genotype is "HET"
+plate_A_B_df <- plate_A_B_df %>%
+  filter(!grepl("HET", genotype))
+
+dim(plate_A_B_df)
+head(plate_A_B_df)
+
+platemap_A_B <-
+        platetools::raw_map(
+            data = as.numeric(plate_A_B_df$seed_density),
+            well = plate_A_B_df$well_position,
+            plate = 96,
+            size = 8
+        ) +
+        theme(plot.title = element_text(size = 10, face = "bold")) +
+        ggplot2::geom_point(aes(shape = plate_A_B_df$genotype)) +
+        ggplot2::scale_shape_discrete(name = "Genotype") +
+        ggplot2::scale_fill_gradient2(
+        name = "Seed Density",
+        low = "white",
+        high = "red",
+        ) 
+
+platemap_A_B
+
+# Load data
+plate_C_file <- file.path(platemap_dir, "platemap_NF1_plate5.csv")
+
+plate_C_df <- readr::read_csv(plate_C_file)
+
+# Remove rows where genotype is "HET"
+plate_C_df <- plate_C_df %>%
+  filter(!grepl("HET", genotype))
+
+dim(plate_C_df)
+head(plate_C_df)
+
+platemap_C <-
+        platetools::raw_map(
+            data = plate_C_df$genotype,
+            well = plate_C_df$well_position,
+            plate = 96,
+            size = 8
+        ) +
+        theme(plot.title = element_text(size = 10, face = "bold")) +
+        ggplot2::scale_fill_discrete(name = "Genotype")  
+
+platemap_C
+
+align_plot <- (
+    platemap_A_B /
+    platemap_C 
+) + plot_layout(heights= c(2,2))
+
+align_plot
+
+supp_fig_2_gg <- (
+  align_plot
+) + plot_annotation(tag_levels = "A") & theme(plot.tag = element_text(size = 20))
+
+# Save or display the plot
+ggsave(output_supp_figure_2, plot = supp_fig_2_gg, dpi = 500, height = 7.75, width = 7)
+
+supp_fig_2_gg

3.figures/supp_figure_2/supp_figure_2.sh

@@ -9,4 +9,4 @@ conda activate nf1_figures
 jupyter nbconvert --to script --output-dir=scripts/ *.ipynb
 
 # run notebooks to generate supplemental figure 2
-Rscript scripts/SuppFigure2_qaulitycontrol.r
+Rscript scripts/SuppFigure2_platemaps.r

3.figures/supp_figure_3/README.md

@@ -0,0 +1,11 @@
+# Creating supplemental figure 3 - Image quality control distributions
+
+To generate the third supplemental figure of the manuscript, there is one step to follow:
+
+1. [SuppFigure3_qualitycontrol.ipynb](./SuppFigure3_qualitycontrol.ipynb): Generate distribution plots for blur and saturation metrics across plate, and patch the plots together to make one figure.
+
+All steps can be ran with the bash script using the command below:
+
+```bash
+source supp_figure_3.sh
+```