I have a dataset with 11 columns with over a 1000 rows each. The columns were labeled V1, V2, V11, etc.. I replaced the names with something more useful to me using the \"c\
You can use negative indexing to remove rows, e.g.:
dat <- dat[-1, ]
Here is an example:
> dat <- data.frame(A = 1:3, B = 1:3)
> dat[-1, ]
A B
2 2 2
3 3 3
> dat2 <- dat[-1, ]
> dat2
A B
2 2 2
3 3 3
That said, you may have more problems than just removing the labels that ended up on row 1. It is more then likely that R has interpreted the data as text and thence converted to factors. Check what str(foo), where foo is your data object, says about the data types.
It sounds like you just need header = TRUE in your call to read in the data (assuming you read it in via read.table() or one of it's wrappers.)