I am completely new to bioinformatics and currently doing this WGCNA analysis from tutorial only. I have used FPKM value for the analysis and while running the second tutorial i have encountered this error (In as.vector(log10(dk)) : NaNs produced), and i don't known what went wrong. so can you suggest how this missing value will further influence the analysis. Thanks for your response

Load the data saved in the first part

lnames = load(file = "FemaleLiver-011-dataInput.RData");

The variable lnames contains the names of loaded variables.

lnames [1] "datExpr" "datTraits"

Choose a set of soft-thresholding powers

powers = c(c(1:10), seq(from = 12, to=20, by=2)) powers [1] 1 2 3 4 5 6 7 8 9 10 12 14 16 18 20

Call the network topology analysis function

sft = pickSoftThreshold(datExpr, powerVector = powers, verbose = 5) pickSoftThreshold: will use block size 2328. pickSoftThreshold: calculating connectivity for given powers... ..working on genes 1 through 2328 of 19212 ..working on genes 2329 through 4656 of 19212 ..working on genes 4657 through 6984 of 19212 ..working on genes 6985 through 9312 of 19212 ..working on genes 9313 through 11640 of 19212 ..working on genes 11641 through 13968 of 19212 ..working on genes 13969 through 16296 of 19212 ..working on genes 16297 through 18624 of 19212 ..working on genes 18625 through 19212 of 19212 Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k. 1 1 0.3340 2.230 0.931 2500.00 2.52e+03 4130 2 2 0.0373 -0.362 0.873 594.00 5.92e+02 1400 3 3 0.3620 -1.350 0.851 202.00 1.84e+02 617 4 4 0.7480 -1.610 0.832 88.20 6.82e+01 413 5 5 0.8590 -1.840 0.827 46.60 2.88e+01 371 6 6 0.8660 -1.770 0.830 28.50 1.34e+01 344 7 7 0.8710 -1.630 0.852 19.50 6.79e+00 324 8 8 0.8660 -1.520 0.855 14.50 3.66e+00 308 9 9 0.8430 -1.440 0.833 11.50 2.06e+00 295 10 10 0.8490 -1.360 0.841 9.54 1.18e+00 285 11 12 0.8540 -1.270 0.850 7.20 4.34e-01 269 12 14 0.8370 -1.210 0.831 5.88 1.73e-01 256 13 16 0.8440 -1.160 0.850 5.03 7.44e-02 245 14 18 0.8530 -1.120 0.860 4.43 3.35e-02 236 15 20 0.8590 -1.090 0.876 3.99 1.57e-02 229 Warning message: In as.vector(log10(dk)) : NaNs produced