[R] Recoding variables based on reference values in data frame

[arun]

Hi,
May be this helps:
Kgeno<- read.table(text="
SNP_ID SNP1 SNP2 SNP3 SNP4
Maj_Allele C G  C  A
Min_Allele T A T G  
ID1 CC    GG    CT    AA
ID2 CC    GG    CC AA
ID3 CC    GG nc  AA
ID4  _  _  _  _ 
ID5 CC    GG    CC    AA
ID6 CC    GG    CC  AA
ID7 CC    GG    CT    AA
ID8 _ _ _ _  
ID9 CT    GG  CC AG
ID10 CC    GG    CC    AA
ID11 CC    GG    CT    AA
ID12 _ _ _ _  
ID13 CC    GG    CC    AA
",sep="",header=TRUE,stringsAsFactors=FALSE)

library(stringr)
library(car)

fun1<- function(x){
 MajMin<- paste0(x[1],x[2])
 MajMaj<-str_dup(x[1],2)
 MinMin<-str_dup(x[2],2)
 recode(x,"'nc'=NA;'_'=NA;MajMaj=0;MajMin=1;MinMin=2")}
sapply(Kgeno[,-1],fun1)

#or

 mat1<-sapply(Kgeno[1:2,-1],function(x) {c(str_dup(x,2),paste(x,collapse=""))})[c(1,3,2),]
sapply(seq_len(ncol(Kgeno[,-1])),function(i) {x<-Kgeno[-c(1:2),-1][,i];as.numeric(factor(x,levels=mat1[,i]))-1})


#Speed comparison
KgenoNew<- rbind(Kgeno[c(1:2),-1],sapply(Kgeno[-c(1:2),-1],rep,1e4))
 system.time(res1<- sapply(KgenoNew,fun1))
#   user  system elapsed 
 #0.672   0.000   0.674 


system.time({
mat1<-sapply(Kgeno[1:2,-1],function(x) {c(str_dup(x,2),paste(x,collapse=""))})[c(1,3,2),]
res2<- sapply(seq_len(ncol(KgenoNew)),function(i){ x<- KgenoNew[-c(1:2),][,i];as.numeric(factor(x,levels=mat1[,i]))-1})
})
#user  system elapsed 
#  0.212   0.000   0.214 
res1New<- res1[-c(1:2),]
res1New1<- as.numeric(res1New)
 dim(res1New1)<- dim(res1New)
identical(res1New1,res2)
#[1] TRUE
A.K.







----- Original Message -----
From: kathleen askland <k.askland at gmail.com>
To: r-help at r-project.org
Cc: 
Sent: Tuesday, July 2, 2013 4:46 PM
Subject: [R] Recoding variables based on reference values in data frame

I'm new to R (previously used SAS primarily) and I have a genetics data
frame consisting of genotypes for each of 300+ subjects (ID1, ID2, ID3,
...) at 3000+ genetic locations (SNP1, SNP2, SNP3...). A small subset of
the data is shown below:
  SNP_ID SNP1 SNP2 SNP3 SNP4  Maj_Allele C G  C  A  Min_Allele T A T G  ID1
CC     GG     CT     AA      ID2 CC     GG     CC AA      ID3 CC     GG
nc
AA      ID4 _ _ _ _  ID5 CC     GG     CC     AA      ID6 CC     GG     CC
     AA      ID7 CC     GG     CT     AA      ID8 _ _ _ _  ID9 CT     GG
CC AG      ID10 CC     GG     CC     AA      ID11 CC     GG     CT     AA
      ID12 _ _ _ _  ID13 CC     GG     CC     AA
The name of the data file is Kgeno.
What I would like to do is recode all of the genotype values to standard
integer notation, based on their values relative to the reference rows
(Maj_Allele and Min_Allele). Standard notation sums the total of minor
alleles in the genotype, so values can be 0, 1 or 2.

Here are the changes I want to make:
1. If the genotype= "nc" or '_" then set equal to NA.
2. If genotype value = a character string comprised of two consecutive
major allele values -- c(Maj_Allele, Maj_Allele) -- then set equal to 0.
3. If genotype  value= c(Maj_Allele, Min_Allele) then set equal to 1.
4. If genotype  value = c(Min_Allele, Min_Allele) then set equal to 2.

I've tried the following ifelse processing but get error (Warning: Executed
script did not end with R session at the top-level prompt.  Top-level state
will be restored) and can't seem to fix the code properly. I've counted the
parentheses. Also, not sure if it would execute properly if I could fix it.

# change 'nc' and '_' to NA, else leave as is:
Kgeno[,2] <- ifelse(Kgeno[,2] == "nc", "NA", Kgeno[,2])
Kgeno[,2] <- ifelse(Kgeno[,2] == "_", "NA", Kgeno[,2])

#convert genotype strings in the first data column to numeric values #(two
major alleles=0, 1 minor and 1 major=1, 2 minor alleles=2), else #leave as
is (to preserve NA values).

Kgeno[,2] <-

ifelse(Kgeno[,2] == noquote(paste(as.character(Kgeno[1,2]), as.character(
Kgeno[1,2]), sep=""), 0,

ifelse(Kgeno[,2] == noquote(paste(as.character(Kgeno[1,2]), as.character(
Kgeno[2,2]), sep=""), 1,

ifelse(Kgeno[,2] == noquote(paste(as.character(Kgeno[2,2]), as.character(
Kgeno[2,2]), sep=""), 2,
            Kgeno[,2])))


Finally, if above code were corrected, this would only change the first
column of data, but I would like to change all 3000+ columns in the same
way.

I would greatly appreciate some suggestions on how to proceed.

Thank you,

Kathleen

---
Kathleen Askland, MD
Assistant Professor
Department of Psychiatry & Human Behavior
The Warren Alpert School of Medicine
Brown University/Butler Hospital

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