Compare data in two rows and replace objects in data frame

x <- read.table(text = "CloneID    genotype2001    genotype2002    genotype2003

# translation key
keyTrans <- c(`11` = 'HT'

require(dplyr)
require(tidyr)
x %>%

On Mon, Aug 4, 2014 at 4:53 AM, raz <barvazduck at gmail.com> wrote:

Dear all,

I have a data frame 144 x 20000 values.
I need to take every value in the first row and compare to the second row,
and the same for rows 3-4 and 5-6 and so on.
the output should be one line for each of the two row comparison.
the comparison is:
if row1==1 and row2==1 <-'HT'
if row1==1 and row2==0 <-'A'
if row1==0 and row2==1 <-'B'
if row1==1 and row2=='-' <-'Aht'
if row1=='-' and row2==1 <-'Bht'

for example:
if the data is:
CloneID    genotype 2001    genotype 2002    genotype 2003
2471250    1    1    1
2471250    0    0    0
2433062    0    0    0
2433062    1    1    1
100021605    1    1    0
100021605    1    0    1
100005599    1    1    0
100005599    1    1    1
100002798    1    1    0
100002798    1    1    1

then the output should be:
CloneID    genotype 2001    genotype 2002    genotype 2003
2471250    A    A    A
2433062    B    B    B
100021605    HT    A    B
100005599    HT    HT    B
100002798    HT    HT    B

I tried this for the whole data, but its so slow:

AX <- data.frame(lapply(AX, as.character), stringsAsFactors=FALSE)


for (i in seq(1,nrow(AX),by=2)){
for (j in 6:144){
if (AX[i,j]==1 & AX[i+1,j]==0){
AX[i,j]<-'A'
}
if (AX[i,j]==0 & AX[i+1,j]==1){
AX[i,j]<-'B'
}
if (AX[i,j]==1 & AX[i+1,j]==1){
AX[i,j]<-'HT'
}
if (AX[i,j]==1 & AX[i+1,j]=="-"){
AX[i,j]<-'Aht'
}
if (AX[i,j]=="-" & AX[i+1,j]==1){
AX[i,j]<-'Bht'
}
}
}

AX1<-AX[!duplicated(AX[,3]),]
AX2<-AX[duplicated(AX[,3]),]

Thanks for any help,

Raz

I don't know if you've received a solution as yet. Below is my generic
solution. I don't know how fast it will be, but it does _NOT_ do any
looping. It does do a few if functions. The result is in the variable
new_data. The variables data_odd and data_even are temporaries which
can be removed. Or you can wrap the code up in a function which
returns new_data and they will simply "go away" when the function
ends.

#
# Read in the data
data <- read.csv(file="data.csv",header=TRUE,stringsAsFactors=FALSE);
#
# The criteria
#if row1==1 and row2==1 <-'HT'
#if row1==1 and row2==0 <-'A'
#if row1==0 and row2==1 <-'B'
#if row1==1 and row2=='-' <-'Aht'
#if row1=='-' and row2==1 <-'Bht'
#
# The following assumes that data is properly ordered!
data$rowNumber <- seq(1:nrow(data));
data_odd <-data[data$rowNumber %% 2 == 1,];
data_even <-data[data$rowNumber %% 2 == 0,];
#
# You really need to make sure that
# the CloneID values are correct in data_odd
# and data_even. Something like:
stopifnot(data_odd$CloneID == data_even$CloneID);
CloneIDs <- data_even[,1]; # Get the list of CloneIDs
#data_even[,1] <- NULL; # Remove CloneIDs from even data
#data_odd[,1] <- NULL;  # And also from odd data
#
# Initialize new_data - make everything NA so
# it will stick out later!
new_data <- data_even;
new_data[,colnames(data_even)] <- NA;
#
new_data[data_odd == 1 & data_odd ==1] <- 'HT';
new_data[data_odd == 1 & data_even == 0] <- 'A';
new_data[data_odd == 0 & data_even == 1] <- 'B';
new_data[data_odd == 1 & data_even == '.'] <- 'Aht';
new_data[data_odd == '-' & data_even == 1] <- 'Bht';
new_data$CloneID <- CloneIDs;
new_data$rowNumber<-NULL;
#
#stopifnot( !is.na(new_data)); # Make sure no NAs left




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