Closed Finesim97 closed 5 years ago
The feature computation should be able to be run in parallel. Every program should generate a csv file, which looks like this:
"comment","feature1here" "A1",100 "B2",200
"comment","feature2here" "B2",0.5 "A1",0.25
"comment","sequence","realmiRNA" "A1","ZZZZZ",0 "B2","XXXX",1
These files then need to be combined: Output:
"comment","sequence","realmiRNA", "feature1here","feature2here" "A1","ZZZZZ",0,100,0.25 "B2","XXXX",1,200,0.5
R provides easy functions to join two data frames: https://www.statmethods.net/management/merging.html
The function in the script should be able to read any number of csv files and combine them. combinecsvfiles <- function(in_files, out_path, real) {
}
done
fi6015
commented
5 years ago fi6015
commented
5 years ago
The feature computation should be able to be run in parallel. Every program should generate a csv file, which looks like this:
These files then need to be combined: Output:
R provides easy functions to join two data frames: https://www.statmethods.net/management/merging.html
The function in the script should be able to read any number of csv files and combine them. combinecsvfiles <- function(in_files, out_path, real) {
code here
}