Update 4 files

- /04_Cytoscape/extract_mrna_names_from_mirna.R
- /04_Cytoscape/extract_mrna_names_from_mirna.Rmd
- /04_Cytoscape/mRNAs.xlsx
- /04_Cytoscape/extract.pdf

04_Cytoscape/extract_mrna_names_from_mirna.R → 04_Cytoscape/extract_mrna_names_from_mirna.Rmd

+---
+output:
+  pdf_document: default
+  html_document: default
+---
+
+```{r LIBRARIES, message=FALSE, warning=FALSE, paged.print=FALSE}
 # Load required libraries
 library(readxl)    # For reading data from Excel files
 library(multiMiR)  # For querying validated miRNA-mRNA interactions
 library(writexl)   # For writing data to Excel files
+```
 
-# Read data from an Excel file named "miRNAmRNA.xlsx" and store it in the "new_list" variable.
-new_list <- read_excel("C:/Users/Emre/Desktop/miRNAmRNA.xlsx", header = TRUE)
+```{r LOAD DATA}
+# Read data from an Excel file named "miRNAmRNA.xlsx" and store it in the "new_list" variable
+new_list <- read_excel("C:/Users/Emre/Desktop/miRNAmRNA.xlsx")
+mirnames <- new_list$miRNA
+```
 
+```{r MULTIMIR}
 # Get validated miRNA-mRNA interactions using the "multiMiR" package.
 # In this case, the interactions are queried for human (hsa) miRNAs (mirnames) from the "validated" table.
 # The results will be summarized and stored in the "multimir_results" variable.
@@ -14,35 +26,30 @@ multimir_results <- get_multimir(org     = 'hsa',
                                  table   = 'validated',
                                  summary = TRUE)
 
-# Display the first few rows of the "multimir_results" data to get an overview of the miRNA-mRNA interactions.
+# Display the first few rows of the "multimir_results" data to get an overview of the miRNA-mRNA interactions
 head(multimir_results@data)
-
-# Extract the results of miRNA-mRNA interactions from the "multimir_results" variable and store them in the "targets" variable.
 targets <- multimir_results@data
 
-# Specify the Excel file path where the results will be saved.
-excel_file <- "C:/Users/Emre/Desktop/Bioinformatik/Bioinformatik 2.Semester Master/Data Science in the Life Sciences/Project/multimir_results.xlsx"
-
-# Write the "targets" data to an Excel file with the specified file path.
-write_xlsx(targets, path = excel_file)
+#excel_file <- "C:/Users/Emre/Desktop/Bioinformatik/Bioinformatik 2.Semester Master/Data Science in the Life Sciences/Project/multimir_results.xlsx"
+#write_xlsx(targets, path = excel_file)
+```
 
-# Read data from the "multimir_results_cyto.xlsx" file into the "df" variable.
-df <- read_excel("C:/Users/Emre/Desktop/multimir_results_cyto.xlsx")
+```{r MRNA FEATURE IMPORTANCE}
+df <- read_excel("C:/Users/Emre/Desktop/multimir_results.xlsx")
 
-# Read data from the "mRNAs.xlsx" file into the "mrna" variable.
+#Read data from the "mRNAs.xlsx" file into the "mrna" variable.
 mrna <- read_excel("C:/Users/Emre/Desktop/mRNAs.xlsx")
+```
 
-# Extract the external gene names from the "mrna" data and store them in the "mrna_genes" variable.
-mrna_genes <-  mrna$external_gene_name
+```{r}
+# Extract the mrna names from the table
+mrna_genes <-  mrna$mRNA
+```
 
+```{r }
 # Filter the "df" data based on whether the "target_symbol" column contains gene names present in the "mrna_genes" variable.
 filtered_df <- df[df$target_symbol %in% mrna_genes | duplicated(df$target_symbol) %in% mrna_genes, ]
 
 # Print the filtered data.
 print(filtered_df)
-
-# Specify the output Excel file path where the filtered data will be saved.
-output_file <- "C:/Users/Emre/Desktop/cytoscape.xlsx"
-
-# Write the filtered data to an Excel file with the specified file path.
-write_xlsx(filtered_df, output_file)
+```