*Combining  2 columns into 1 column many times in a very large dataset*

The clumsy solutions I am working on are not going to be very fast if I can
get them to work and the true dataset is ~1500 X 45000 so they need to be
efficient. I've searched the R help files and the archives for this list and
have some possible workable solutions for 2) and 3) but not my question 1).
However, I include 2) and 3) in case anyone has recommendations that would
be efficient.

Here is a toy example of the data structure:
pop = data.frame(status = rbinom(n, 1, .42), sex = rbinom(n, 1, .5),
age = round(rnorm(n, mean=40, 10)), disType = rbinom(n, 1, .2),
rs123=c(1,3,1,3,3,1,1,1,3,1), rs123.1=rep(1, n),
rs157=c(2,4,2,2,2,4,4,4,2,2),
rs157.1=c(4,4,4,2,4,4,4,4,2,2),  rs132=c(4,4,4,4,4,4,4,4,2,2),
rs132.1=c(4,4,4,4,4,4,4,4,4,4))

Thus, there are a few columns of basic demographic info and then the rest of
the columns are biallelic SNP info.  Ex: rs123 is allele 1 of rs123 and
rs123.1 is the second allele of rs123.

1) I need to merge all the biallelic SNP data that is currently in 2 columns
into 1 column, so, for example: rs123 and rs123.1 into one column (but
within the dataset):
11
31
11
31
31
11
11
11
31
11
2) I need to identify the least frequent SNP value (in the above example it
is 31).
3) I need to replace the least frequent SNP value with 1 and the other(s)
with 0.

Thank you for any assistance,
-S.R.

	[[alternative HTML version deleted]]

