Hi Stefanie,
I encountered an error running the summary() on the netcompare output:
in if (x > 0.1) { : missing value where TRUE/FALSE needed, which traces back to .getSigCode(object$pvalDiffGlobalLCC[[paste0("pval", glob_names_lcc2[i])]])
I think it may be related to the average path length being Inf as shown by summarizing the netAnalyze output.
Largest connected component (LCC): Passage 1 Passage 4 Relative LCC size 0.57500 0.42500 Clustering coefficient 0.73815 0.75341 Modularity 0.39967 0.37175 Positive edge percentage 64.64646 68.18182 Edge density 0.23575 0.16399 Natural connectivity 0.20375 0.15528 Vertex connectivity 1.00000 1.00000 Edge connectivity 1.00000 1.00000 Average dissimilarity* 0.82861 0.87249 Average path length** 1.65353 Inf
The pipeline was:
`
netCon = netConstruct(data = CB_community[1][[1]],
data2 = CB_community[i][[1]],
jointPrepro = F,
taxRank = "Species",
#filtTax = "highestFreq",
#filtTaxPar = list(highestFreq=50),
measure = "sparcc",
measurePar = list(iter=50, inner_iter = 50, th=0.4),
normMethod = "clr",
sparsMethod = "threshold",
thresh = 0.9,
zeroMethod = "multRepl",
adjust = "adaptBH",
verbose = 2,
seed = 123)
netAnna = netAnalyze(netCon,
centrLCC = TRUE,
clustMethod = "cluster_fast_greedy",
hubPar = c("degree", "eigenvector"),
hubQuant = 0.9,
lnormFit = T,
weightDeg = FALSE,
normDeg = T,
normBetw = T,
normClose = T,
normEigen = T,
graphlet = F
)
netComp.CB_p1vsp4 = netCompare(CB_p1vsp4,
permTest = T,
nPerm = 20,
verbose = T,
gcd = F, seed = 12)
`
Is there a way I could resolve this error?
Best,
Xio
Hi Stefanie,
I encountered an error running the summary() on the netcompare output:
in if (x > 0.1) { : missing value where TRUE/FALSE needed, which traces back to.getSigCode(object$pvalDiffGlobalLCC[[paste0("pval", glob_names_lcc2[i])]])I think it may be related to the average path length being
Infas shown by summarizing the netAnalyze output.Largest connected component (LCC): Passage 1 Passage 4 Relative LCC size 0.57500 0.42500 Clustering coefficient 0.73815 0.75341 Modularity 0.39967 0.37175 Positive edge percentage 64.64646 68.18182 Edge density 0.23575 0.16399 Natural connectivity 0.20375 0.15528 Vertex connectivity 1.00000 1.00000 Edge connectivity 1.00000 1.00000 Average dissimilarity* 0.82861 0.87249 Average path length** 1.65353 InfThe pipeline was:
`
netCon = netConstruct(data = CB_community[1][[1]],
data2 = CB_community[i][[1]],
jointPrepro = F,
taxRank = "Species",
#filtTax = "highestFreq",
#filtTaxPar = list(highestFreq=50),
measure = "sparcc",
measurePar = list(iter=50, inner_iter = 50, th=0.4),
normMethod = "clr",
sparsMethod = "threshold",
thresh = 0.9,
zeroMethod = "multRepl",
adjust = "adaptBH",
verbose = 2,
seed = 123)
netAnna = netAnalyze(netCon,
centrLCC = TRUE,
clustMethod = "cluster_fast_greedy",
hubPar = c("degree", "eigenvector"),
hubQuant = 0.9,
lnormFit = T,
weightDeg = FALSE,
normDeg = T,
normBetw = T,
normClose = T,
normEigen = T,
graphlet = F
)
netComp.CB_p1vsp4 = netCompare(CB_p1vsp4,
permTest = T,
nPerm = 20,
verbose = T,
gcd = F, seed = 12)
`
Is there a way I could resolve this error?
Best,
Xio