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I'm trying to run the GRNBoost2 - GRN algorithm on a matrix of shape (11744, 9031) in my cluster of 104GB RAM / Intel(R) Xeon(R) CPU @ 2.30GHz / 16 CPU (s). So far it's running for +20h.
I have a couple of questions:
Should I use the raw expression matrix? Or should I use the log-transformed/normalized expression matrix?
I don't have the list of TF? Can I put all the genes present in the dataset? Or leave it blank?
Thanks in advance for any help!
Best,
Francisco Grisanti
The text was updated successfully, but these errors were encountered:
I have this problem every time I do a run,. When I try a run on data 2835 cells by 26048 genes it will run for a week before I abandon it (Intel(R) Core(TM) i7-10610U CPU @ 1.80GHz 2.30GHz 64.0GB installed RAM). I always cut the data down with highly_variable genes to about 30M elements (eg. 7K genes if I have 4K cells) to get it to run within a reasonable time frame. I always wonder if I am losing important data when doing that ...
Hi!
I'm trying to run the GRNBoost2 - GRN algorithm on a matrix of shape (11744, 9031) in my cluster of 104GB RAM / Intel(R) Xeon(R) CPU @ 2.30GHz / 16 CPU (s). So far it's running for +20h.
I have a couple of questions:
Should I use the raw expression matrix? Or should I use the log-transformed/normalized expression matrix?
I don't have the list of TF? Can I put all the genes present in the dataset? Or leave it blank?
Thanks in advance for any help!
Best,
Francisco Grisanti
The text was updated successfully, but these errors were encountered: