ParseBuscoResults <- function(busco_dir, length_threshold = 0.25){
busco_folders <- dir(busco_dir)[grep("run_", dir(busco_dir))] #refresh this here as new runs may have been created at STEP 2
final_columns <- 'busco_id' #initialize the final column names
pb3 <- txtProgressBar(min = 0, max = length(busco_folders), style = 3)
for (n in 1:length(busco_folders)){
sub_busco <- gsub("run_", "", busco_folders[n])
table_to_read <- paste(busco_dir, "/", busco_folders[n], "/full_table_", sub_busco, ".tsv", sep = "") #need to get species list in this function
MyData <- read.delim(table_to_read, skip = 4, header = TRUE, sep = "\t", fill = TRUE, na.strings = "NA")
if (exists("row_names") == FALSE){ #if it doesn't exist, create it
row_names <- unique(MyData[,1]) #get the row names only the first pass through
}
if (exists("parsed_busco_df") == FALSE){ #if it doesn't exist, create it
MyInitial <- data.frame(row_names, NA) #add the row_names to the final data
matrix_holder <- MyInitial[,1]
parsed_busco_df <- data.frame(matrix_holder)
}
final_columns <- append(final_columns, sub_busco)
MyCleanData <- data.frame(NULL)
targets<-unique(MyData[,1])
#remove reads less than the desired percent of the max read length for this species
MyData <- MyData[which(MyData$Length > (max(MyData$Length, na.rm=T)*length_threshold)),]
for (i in 1:length(targets)){
specific_species <- MyData[which(MyData[,1]==targets[i]),]
target_value <- max(specific_species$Score)
row_needed <- specific_species[which(specific_species$Score==target_value),]
MyCleanData <- rbind(MyCleanData,row_needed[1,]) #if scores above were identical, this grabs just the first one
}
setTxtProgressBar(pb3, n)
parsed_busco_df <- cbind(parsed_busco_df,MyCleanData[,3]) #tosses out warnings when all are missing but this is fine to ignore
}
close(pb3)
names(parsed_busco_df) <- final_columns #rename the columns based on the order they were parsed
return(parsed_busco_df)
}
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