Closed iadamo1 closed 2 years ago
Technically, there's no minimum number of samples, however, from a statistical point of view, such small sample sizes are not meaningful. You won't get reliable association estimates with only a few samples.
The message "Network is empty" means that all estimated associations are zero after sparsification.
Also, Spring's built-in stability-based model selection approach is not meaningful for such small sample sizes. Setting rep.num to 50 means that 50 times, subsamples are taken and associations estimated. With only 4 samples, there is no variability in the subsamples.
Best, Stefanie
Thanks for your reply! Yes, I actually merged the samples in order to be able to construct the network and have enough variability. I had also changed the nlamba and num.rep to higher values.
Hi,
I am wondering whether you need a minimus number of samples when you run this: net_single <- netConstruct(amgut1.filt, filtTax = "highestFreq", filtTaxPar = list(highestFreq = 100), filtSamp = "totalReads", filtSampPar = list(totalReads = 1000), measure = "spring", measurePar = list(nlambda=10, rep.num=10), normMethod = "none", zeroMethod = "none", sparsMethod = "none", dissFunc = "signed", verbose = 3, seed = 123456) I have changed the nlamba and rep.num to 50 for my data.
The thing is I have four samples and then I get this message for my data: Error in netAnalyze(net_singlehal, clustMethod = "cluster_fast_greedy") : Network is empty.
Thanks a lot