module_preservation {BioNERO} | R Documentation |
Calculate network preservation between two expression data sets
module_preservation( explist, ref_net = NULL, test_net = NULL, algorithm = "netrep", nPerm = 1000, nThreads = 1, plot_all_stats = FALSE )
explist |
List of SummarizedExperiment objects or expression data frames with genes (or orthogroups) in row names and samples in column names. |
ref_net |
Reference network object returned by
the function |
test_net |
Test network object returned by the function |
algorithm |
Module preservation algorithm to be used. One of 'netrep' (default, permutation-based) or WGCNA. |
nPerm |
Number of permutations. Default: 1000 |
nThreads |
Number of threads to be used for parallel computing. Default: 1 |
plot_all_stats |
Logical indicating whether to save all density and connectivity statistics in a PDF file or not. Default: FALSE. |
A list containing the preservation statistics (netrep) or a ggplot
object with preservation statistics.
See WGCNA::modulePreservation
or NetRep::modulePreservation
for more info.
set.seed(1) data(og.zma.osa) data(zma.se) data(osa.se) og <- og.zma.osa exp_ortho <- exp_genes2orthogroups(explist, og, summarize = "mean") exp_ortho <- lapply(exp_ortho, function(x) filter_by_variance(x, n=1500)) # Previously calculated SFT powers powers <- c(13, 15) gcn_osa <- exp2gcn(exp_ortho$osa, net_type = "signed hybrid", SFTpower = powers[1], cor_method = "pearson") gcn_zma <- exp2gcn(exp_ortho$zma, net_type = "signed hybrid", SFTpower = powers[2], cor_method = "pearson") explist <- exp_ortho ref_net <- gcn_osa test_net <- gcn_zma # 10 permutations for demonstration purposes pres <- module_preservation(explist, ref_net, test_net, nPerm=10)