remove duplicate rows based on conditions from multiple columns in r

Question

I have a data set I would like to remove the rows of data that have duplicate information in 4 different columns.

foo<- data.frame(g1 = c("1","0","0","1","1"), v1 = c("7","5","4","4","3"), v2 = c("a","b","x","x","e"), y1 = c("y","c","f","f","w"), y2= c("y","y","y","f","c"), y3 = c("y","c","c","f","w"), y4= c("y","y","f","f","c"), y5=c("y","w","f","f","w"), y6=c("y","c","f","f","w"))

foo then looks like:

  g1 v1 v2 y1 y2 y3 y4 y5 y6
1  1  7  a  y  y  y  y  y  y
2  0  5  b  c  y  c  y  w  c
3  0  4  x  f  y  c  f  f  f
4  1  4  x  f  f  f  f  f  f
5  1  3  e  w  c  w  c  w  w

Now, I want to remove any row that has duplicated data based on the Y1-6columns. So, only row 4 and 1 would be removed if done properly, based on all Y variables being the exact same. Its a multiple column condition.

I believe I am close, but its just not working correctly.

I have tried: new = foo[!(duplicated(foo[,1:6]))] thinking to use the duplicated command that it would search and only find those that matched exactly?

I thought about using a conditional statement with &, but can't figure out how to do that either.
new = foo[foo$y1==foo$y2|foo$y3|foo$y4|foo$y5|foo$y6]

I thought about which but Im now overwhelmed and lost. I would expect foo to look like:

   g1 v1 v2 y1 y2 y3 y4 y5 y6
2  0  5  b  c  y  c  y  w  c
3  0  4  x  f  y  c  f  f  f
5  1  3  e  w  c  w  c  w  w

Answer 1

> foo[apply(foo[ , paste("y", 1:6, sep = "")], 1,
            FUN = function(x) length(unique(x)) > 1 ), ]
  g1 v1 v2 y1 y2 y3 y4 y5 y6
2  0  5  b  c  y  c  y  w  c
3  0  4  x  f  y  c  f  f  f
5  1  3  e  w  c  w  c  w  w

Answer 2

> foo[ !rowSums( apply( foo[2:6], 2, "!=", foo[1] ) )==0, ]
  y1 y2 y3 y4 y5 y6
2  c  y  c  y  w  c
3  f  y  c  f  f  f
5  w  c  w  c  w  w

> foo[ ! colSums( apply( foo, 1, duplicated, foo[1] ) ) == 5, ]
  y1 y2 y3 y4 y5 y6
2  c  y  c  y  w  c
3  f  y  c  f  f  f
5  w  c  w  c  w  w

Answer 3

foo[apply(foo, 1, function(x) any(x != x[1])),]