I'm using the software of Mfuzz. And it's a very useful method for clustering. But I got some problems when using it. I have an expression matrix stored as table in the file like this. Same format with the examples "yeast.table".

#GENE.ID    S1_1    S2_1    S3_1    S4_1    S5_1    S6_1
#TIME   1   2   3   4   5   6
#ENSSG13342 3.563908454 3.636868307 3.757429854 3.487813157 3.924786191 4.050614183
#ENSSG01130 0.816725847 0.233591149 0.045866491 0.081422805 0.078299677 0.063410441
#ENSSG18225 1.586500075 1.961881101 0.428823101 1.447323694 1.463457149 2.587627581
#ENSSG11910 0.649597066 0.882924714 0.001441974 1.22588446  1.161404661 0.550070261

But when I begin to run, it return some errors as below.

#> yeast<-table2eset(file="test2.txt")
#Read 7 items
#Read 7 items
#Read 7 items
#> yeast.r <- filter.NA(yeast, thres=0.25)
#0 genes excluded.
#> yeast.f <- fill.NA(yeast.r,mode="mean")
#> yeast.s <- standardise(yeast.f)
#> m1 <- mestimate(yeast.s)
#> m1 # xx
#[1] 1.71159
#> cl <- mfuzz(yeast.s,c=16,m=1.71)
#***Error in cmeans(exprs(eset), centers = centers, method = "cmeans", m = m, :
#  NA/NaN/Inf in foreign function call (arg 1)***
#> yeast.s
#ExpressionSet (storageMode: lockedEnvironment)
#assayData: 19189 features, 6 samples
#  element names: exprs
#protocolData: none
#phenoData
#  sampleNames: S1_1 S2_1 ... S6_1 (6 total)
#  varLabels: time
#  varMetadata: labelDescription
#featureData: none
#experimentData: use 'experimentData(object)'
#Annotation:
#> yeast
#ExpressionSet (storageMode: lockedEnvironment)
#assayData: 19189 features, 6 samples
#  element names: exprs
#protocolData: none
#phenoData
#  sampleNames: S1_1 S2_1 ... S6_1 (6 total)
#  varLabels: time
#  varMetadata: labelDescription
#featureData: none
#experimentData: use 'experimentData(object)'
#Annotation:
#> traceback()
#3: .C(R_cmeans, as.double(x), as.integer(xrows), as.integer(xcols),
#       centers = as.double(centers), as.integer(ncenters), as.double(weights),
#       as.double(m), as.integer(dist - 1), as.integer(iter.max),
#       as.double(reltol), as.integer(verbose), u = double(xrows *
#           ncenters), ermin = double(1), iter = integer(1))
#2: cmeans(exprs(eset), centers = centers, method = "cmeans", m = m,
#       ...)
#1: mfuzz(yeast.s, c = 16, m = 1.71)

I don't know what's the problem of it. Can someone help me to solve this problem? Thanks a lot.