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am importing the same targetsets from the multimir-Package with different cutoffs.
Right now, I am using a loop to import the same targetsets multiple times but with different cutoffs:
miDB <- "pita"
cutoff <- c( 20,80,95,98,99)
for (DB in miDB) {
for (miCutOff in cutoff) {
miRNA_target_db = get_multimir(mirna=grouped_ID2, org="mmu", table=miDB, predicted.cutoff=miCutOff, summary=FALSE)
}
}
That´s a mock-up of the code I am using. The problem is, that importing the data takes between 2-5 minutes depending on the targetset and the cutoff. Is there a way to import the data once with a cutoff of 99 (for example) and then change the cutoff to 98,95,80 and so on?
The text was updated successfully, but these errors were encountered:
@SergejRuff I apologize for the delayed response. There is no functionality to make this work right now. Each run of get_multimir constructs the SQL query and sends it to the server to query the database which returns HTML tables that are parsed in R.
I will be spending some time on the database to provide updated data, but we are not planning major revisions of the R package. I will mention this request and see if it's something we could find a way to accommodate.
am importing the same targetsets from the multimir-Package with different cutoffs.
Right now, I am using a loop to import the same targetsets multiple times but with different cutoffs:
miDB <- "pita"
cutoff <- c( 20,80,95,98,99)
for (DB in miDB) {
for (miCutOff in cutoff) {
miRNA_target_db = get_multimir(mirna=grouped_ID2, org="mmu", table=miDB, predicted.cutoff=miCutOff, summary=FALSE)
}
}
That´s a mock-up of the code I am using. The problem is, that importing the data takes between 2-5 minutes depending on the targetset and the cutoff. Is there a way to import the data once with a cutoff of 99 (for example) and then change the cutoff to 98,95,80 and so on?
The text was updated successfully, but these errors were encountered: