MEBA time-series error message in R

Hi Xia Lab,

I am currently running time-series data and want to perform a MEBA. My code works completely fine with some data tables loaded as CSV and for other tables which have the exact same data format and - I checked it a couple of times - are balanced between groups I get the following error message:

Error in my.time.mb.2d(object, k, mn, c.grp, nu, Lambda, eta, k.grp, mn.grp, :
The sample sizes or the biological condition group assignments are incorrect!

I checked the groups several times in the data table as well as in the meta file. It is correct, and also works for other data tables that I load. Do you know any reason that I could get this error message? Here is the code I use:

mSet<-InitDataObjects(“pktable”, “mf”, FALSE)
mSet<-SetDesignType(mSet, “time”)
mSet<-Read.TextDataTs(mSet, “mydirectory.csv”, “rowmf”);
mSet<-ReadMetaData(mSet, “mydirectory.csv”);
mSet<-SanityCheckData(mSet)
mSet<-ReplaceMin(mSet);
mSet<-SanityCheckMeta(mSet, 1)
mSet<-SetDataTypeOfMeta(mSet);
mSet<-SanityCheckData(mSet)
mSet<-FilterVariable(mSet, “median”, 0, “F”, 25, F)
mSet<-PreparePrenormData(mSet)
mSet<-Normalization(mSet, “MedianNorm”, “NULL”, “AutoNorm”, ratio=FALSE, ratioNum=20)

meta.vec.mb ← c(“Phenotype”, “Time”)
mSet<-performMB(mSet, 10)

Sanity check is without any problems and it completely works with other data tables. I made copies of this data table, named the variables differently, used a statistical filter, looked at everything in the mSet object - it looks all fine. I don’t find the problem.

It would be great, if you have an idea.

Thanks
David

It is probably something within my data, which I can not post here that causes this error rather than the code since it works fine for other data tables. So my question is rather in the direction if you could think of something that could cause this error other than “unbalanced” groups. Thanks

Found a mistake. I’ll close it. Sorry.

This topic was automatically closed 12 hours after the last reply. New replies are no longer allowed.