Hi,
Basically we have a spreadsheet containing all our microarray data, genes in rows and samples in colums. We have 6 batches in total, each containing 5-8 samples (53 samples in total) that were run on 5 different microarrays. I also created a SIF.csv file containing 3 columns : Array, Sample, Batch (See head and tail below). Array goes from 1 to 6, Batch goes from 1 to 6 and sample contains the name of each sample (same as in the spreadsheet). When running combat it generates some error.. The tutorial and manual is custom for a certain type of data and didn't help me understand how to apply this to more universal type of data. I don't understand how to get run combat, it constantly generates errors. What am I doing wrong with the script below?
> head(sif)
Array Sample Batch
1 Array1 Sample1 Batch1
2 Array1 Sample2 Batch1
3 Array1 Sample3 Batch1
4 Array1 Sample4 Batch1
5 Array1 Sample5 Batch1
6 Array1 Sample6 Batch1
> tail(sif)
Array Sample Batch
48 Array6 Sample48 Batch6
49 Array6 Sample49 Batch6
50 Array6 Sample50 Batch6
51 Array6 Sample51 Batch6
52 Array6 Sample52 Batch6
53 Array6 Sample53 Batch6
> library(sva)
> dat = read.csv("Combat_matrix_input.csv");
> sif = read.csv("sif.csv");
> modcombat = model.matrix(~1, data=dat)
# Here I run combat as per the tutorial
> combat_edata = ComBat(dat, batch=batch, mod=modcombat, par.prior=TRUE, prior.plots=FALSE)
Found 6 batches
Error in cbind(batchmod, mod) :
number of rows of matrices must match (see arg 2)
#I was suspecting that the error was coming from mod, so I set it to NULL
> combat_edata = ComBat(dat, batch=batch, mod=NULL, par.prior=TRUE, prior.plots=FALSE)
Found 6 batches
Adjusting for 0 covariate(s) or covariate level(s)
Standardizing Data across genes
Error in solve(t(design) %*% design) %*% t(design) %*% t(as.matrix(dat)) :
requires numeric/complex matrix/vector arguments
I should also say that using model.matrix(~1,...) is equivalent to the default mod = NULL. Unless you have actual covariates, you can leave mod at the default value.