FASTA_R

#FASTA Query for Proteomics

#This script is designed for Rstudio and encapsulates a function to pull data from FASTA files from UniProt database. #A resulting dataframe will include select data based on specifications.

Define a function that processes a FASTA file and finds shared protein entries

process_fasta_file <- function(fasta_file_path, comparison_df, output_file_name) {

Check for the comparison data frame and its 'id' column

if (missing(comparison_df) || !"id" %in% names(comparison_df)) { stop("The comparison data frame is missing or does not have an 'id' column - rename applicable column.") }

Read the FASTA file

fasta_data <- readAAStringSet(fasta_file_path)

Extract the headers

headers <- names(fasta_data)

Extract UniProt names and gene names

uniprot_names <- sub(".\|(.?)\|.", "\1", headers) collapsed_names <- sub(".\|.?\|(.?)\s.*", "\1", headers) gene_names <- sub(".GN=(\w+).", "\1", headers)

Store results in a data.frame

result_df <- data.frame(Header = headers, UniProt_Name = uniprot_names, Collapsed_Name = collapsed_names, Gene_Name = gene_names, stringsAsFactors = FALSE)

Find shared entries

shared_entries <- intersect(result_df$UniProt_Name, comparison_df$id)

Print and write shared entries

print(shared_entries)

if (!missing(output_file_name)) { write.table(shared_entries, output_file_name, sep=",", row.names=FALSE, quote=FALSE) }

Return the result data frame and the shared entries

return(list(Result_DataFrame = result_df, Shared_Entries = shared_entries)) }

Invoke the function

#In this example the .gz FASTA file was downloaded from the UniProt database and unzipped #In order: file path specification, modify Your_df with the name of the pre-existing dataframe, and the desired name for the result shared_entries_cu <- process_fasta_file("uniprotkb_copper_binding_proteins_AND_m_2023_11_03.fasta.gz",Your_df, "Desired_Resulting_df.csv")