Row-wise sum of values grouped by columns with same name

We can transpose dat , calculate rowsum per group (colnames of the original dat), then transpose the result back to original structure.

t(rowsum(t(dat), group = colnames(dat), na.rm = T))
#  A C G T
#1 1 0 1 0
#2 4 0 6 0
#3 0 1 0 1
#4 2 0 1 0
#5 1 0 1 0
#6 0 1 0 1
#7 0 1 0 1

We could split the dataframe by name using split.default and take the row-wise sum using rowSums to create one column for each unique name.

sapply(split.default(df, names(df)), rowSums, na.rm = TRUE)

#  A C G T
#1 1 0 1 0
#2 4 0 6 0
#3 0 1 0 1
#4 2 0 1 0
#5 1 0 1 0
#6 0 1 0 1
#7 0 1 0 1