I created a dummy data set for this. Please go through the code below and try to compare with your code. Probably the data structure in R might be incorrect. Check your data types. I added comments to the code. Simulated data has 4 times points (1-4) and two conditions (Normal and tumor represented by A and B respectively). Gene names are 4 (gene1-4). Hence data frame is 4x8. Compare your data frame with final data frame in the example (name: total_exp)

$ library(timecourse)

## Create 4 normal sample microarray names
$ normal=paste("A_",seq(1:4),".cel", sep="")

## Create 4 tumor sample microarray names
$ tumor=paste("B_",seq(1:04),".cel", sep="")

## create row names to be used for dataframe
$ genes=paste("gene",seq(1:4),sep="")

## Create expression data for 4 normal samples for 4 time points
$ normal_exp=matrix(rnorm(16,100,25),4,4)

## Create expression data for 4 tumor samples for 4 time points
$ tumor_exp=matrix(rnorm(16,100,50),4,4)

## Assign column names to normal expression data
$ colnames(normal_exp)=normal

## Assign row names to tumor expresion data
$ colnames(tumor_exp)=tumor

## Append two data frames next to each other
$ total_exp=cbind(normal_exp, tumor_exp)

## Make gene names as row names for entire data
$ row.names(total_exp)=genes

## Run mb.long. Times= time points for each category (normal-4, tumor-4), reps= total
## number of conditions multiplied by number of rows (observations)    
$ out1=mb.long(total_exp, times=4, reps=rep(2,4))

## Run mob.long with more control. For times and reps look above. Rep.grp= Each
## condition is repeated by number of replicates (4) time.grp= each sample number 
## (1:4) is repeated condition times (2 here)
$ out2 <- mb.long(total_exp, times=4, reps=rep(2,4), rep.grp=rep(c("Normal", "Tumor"), each=4), time.grp=rep(c(1:4),2))