replace with quantile value for a large data frame...

Dear R-Experts

I am sure this might look simple question for experts, at least is problem
for me. I have a large data frame with over 1000 variables and each have
different distribution( i.e. have different quantile). I want to create a
new grouped data frame, where the new variables where the value falling in
first (<25%), second (25% to<50%), third (50% to<75%) and fourth quantiles
(>75%) are replaced with 1,2,3, 4 respectively. The following example is
just to workout.
# my example:
    X1<- c(1:10)

X2<- c(11:20)
X3<- c(21:30)
X4<- c(31:40)
X5<- c(41:50)
dataf<- data.frame(X1, X2, X3, X4, X5)

# my efforts of the last week led me to this point

for (i along(length(dataf[1,]))) {

qntfun<- function (x) {
   XQ<- as.numeric(as.matrix(quantile(x)))
   Q1<- XQ[1]
   Q2<- XQ[2]
   Q3<- XQ[3]
   Q4<- XQ[4]
   for (i in 1:length(x)){
   if (x[i]<  Q2) {
               x[i]<- 1
               } else {
               if ( x[i]>  Q2&  x[i]<  Q3){
               x[i]<- 2
               }   else {
               if ( x[i]>Q3&  x[i]<Q4) {
               x[i]<- 3
               } else {
               if (x[i]>  Q4) {
               x[i]<- 4
               } else{
                x[i]<- 0
               }
               }
               }
               }
               }
               }
apply(dataf, 1:length(dataf), qntfun)
  }

# I got error, I can not fix it. I would be glad to see a more slim
solution, but I could not think any.

Thanks in advance for your help.

Ram Sharma

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