revisions

working directory set automatically

Heatmaps_embryo_code/Make_embryo_heatmap_even-skipped.R

@@ -4,15 +4,13 @@ library(scales)
 # Code to generate whole embryo heatmap variability
 # Only eve is used for this example but the code will be the same for all the other genes
 
-# First you need to make sure your working directory is the same as where the raw data is. 
-# For that you will go to the the folder where your computer downloaded the git and 
-# Use the comand bellow to establish that folder as your working directory in R 
-
-setwd("~/Downloads/smiFISH_Arthropods-main/Neighbours_finding/Raw_data") #Example of where the folder was downloaded in a mac
+# Use the comand bellow to establish the main folder of neighbour finding as your working directory
+setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) #Automatically set working directory
+setwd('..') # Automatically go one level up current working directory
 print(getwd())
 
 # Load the variability data for even-skipped
-eve <- read.csv("Figure5_Variability_Calculations_eve.csv")
+eve <- read.csv("./Neighbours_finding/Raw_data/Figure5_Variability_Calculations_eve.csv")
 
 x = eve[,2]
 y = eve[,3]

Neighbours_finding/Neigbour_finding_eucledian_distance.R

@@ -5,18 +5,18 @@ library(tidyr)
 library(data.table) 
 
 
-# First you need to make sure your working directory is the same as where the raw data is. 
-# For that you will go to the the folder where your computer downloaded the git and 
-# Use the comand bellow to establish that folder as your working directory in R
+# Use the comand bellow to establish the main folder of neighbour finding as your working directory
+
+setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) # Automatically set working directory
 
-setwd("~/Downloads/smiFISH_Arthropods-main/Neighbours_finding/Raw_data") #Example of where the folder was downloaded in a mac
 print(getwd())
 
+
 # Using spectrin cells were segmented in Imaris and each cell is given 
 # a position in X,Y,Z that is their center point
 # Import the cell middle position onto R 
 
-df <- read.csv("Figure5_Cells_XYZ_Positions.csv")
+df <- read.csv("./Raw_data/Figure5_Cells_XYZ_Positions.csv")
 rownames(df) <- df[,1]
 df=df[,-1]
 

Neighbours_finding/Neigbour_finding_polygons.R

@@ -5,22 +5,20 @@ library(data.table)
 library(sf)
 
 
+# Use the comand bellow to establish the main folder of neighbour finding as your working directory
 
-# First you need to make sure your working directory is the same as where the raw data is. 
-# For that you will go to the the folder where your computer downloaded the git and 
-# Use the comand bellow to establish that folder as your working directory in R 
+setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) #Automatically set working directory
 
-setwd("~/Downloads/smiFISH_Arthropods-main/Neighbours_finding/Raw_data") #Example of where the folder was downloaded in a mac
 print(getwd())
 
 # this will print your working directory, the output should look like this:
-# "~/SOMEWHERE_IN_YOUR_COMPUTER/smiFISH_Arthropods-main/Supplemental_files"
+# "~/SOMEWHERE_IN_YOUR_COMPUTER/smiFISH_Arthropods-main/Neighbours_finding"
 
 
-# Import measurements from Imaris onto R. 
+# Import measurements from Imaris onto R, located in Raw_data
 # The starting data frame of (x,y,z) positions of Spectrin spots was obtained from Imaris 
 # by segmenting Spectrin antibody staining. Each cell is composed of several spots of spectrin signal around the membrane
-df_80k <- read.csv('Figure4_80K_Spectrin_Spots_XYZ_Positions.csv')
+df_80k <- read.csv('./Raw_data/Figure4_80K_Spectrin_Spots_XYZ_Positions.csv')
 
 #Change column names
 colnames(df_80k) <- c("Cell_ID", "Spot_ID", "X", "Y", "Z")
@@ -78,6 +76,7 @@ results_80k_0.6 = a2_80k_0.6%>%
     mutate(rn = rowid(Cell_ID)) %>%
     pivot_wider(names_from = rn, values_from = Cell_ID.1)
 
+head(results_80k_0.6)
 
 #Save results as a table that you could use in excel and visualize outside R
 write.csv(results_80k_0.6, "2020.11.16_results_polygons_80k_exp_0.6.csv", na="", row.names=FALSE)

Neighbours_finding/Process_neighbours_finding.R

@@ -1,6 +1,6 @@
 # Once neighbours have been identified by following any of the previously used tutorial 
 # (neighbours finding polygons or neighbours finding eucledian distance)
-# this tutorial could be followed to replace the neighbours' cells 
+# this tutorial could be followed to replace the neighbours cells 
 # by their mRNA content for statistic purpose. 
 
 
@@ -10,12 +10,9 @@ library(dplyr)
 library(tidyr) 
 library(data.table) 
 
+# Use the comand bellow to establish the main folder of neighbour finding as your working directory
+setwd(dirname(rstudioapi::getActiveDocumentContext()$path)) #Automatically set working directory
 
-# First you need to make sure your working directory is the same as where the raw data is. 
-# For that you will go to the the folder where your computer downloaded the git and 
-# Use the comand bellow to establish that folder as your working directory in R 
-
-setwd("~/Downloads/smiFISH_Arthropods-main/Neighbours_finding/Raw_data") #Example of where the folder was downloaded in a mac
 print(getwd())
 
 #Load the results table on R and change the values of the neighbours 
@@ -29,7 +26,7 @@ print(getwd())
 
 #Load both datasets 
 df <- read.csv("2020.11.16_results_polygons_80k_exp_0.6.csv")
-gt <- read.csv("Figure4_gt_Spots.csv")
+gt <- read.csv("./Raw_data/Figure4_gt_Spots.csv")
 
 # Get first few lines of each dataframe
 head(df)