Question

I have large set will a number of variables:

set.seed (14)
pool = sample (c("AA","AB", "BB"), 100, replace = T) 
mydf <- data.frame (M1= pool[1:10], M2= pool[11:20],
M3= pool[21:30], M4= pool[31:40],  M5= pool[41:50], 
  M6= pool[51:60],  M7= pool[61:70], M8 = pool[71:80], 
  M9 = pool[81:90],  M10 = pool[91:100])

Need to install the package “hapassoc”, if previously installed.

install.packages(“hapassoc”)

>  library(hapassoc)
> example1.haplos <- pre.hapassoc(mydf, numSNPs = 3, allelic= F)

Haplotypes will be based on the following SNPs (genotypic format): 
 M8, M9, M10 
Remaining variables are: 
 M1, M2, M3, M4, M5, M6, M7

It is taking last 3 variables in group. But 1 want apply this function by breaking data into smaller pieces by group –

M1, M2, M3   group 1
M4, M5       group 2
M6, M7, M8   group 3
M9, M10      group 4 

Thus numSNPs would be represented by the following vector:

nsp <- c(3, 2, 3, 2)

I want to preserve the $haploMat for each group

example1.haplos$haploMat
 haplo1 haplo2
1    hBBA   hBAB
3    hAAB   hABB
4    hABA   hABA
6    hAAA   hBBA
7    hAAA   hAAA
8    hBBA   hBBB
9    hABB   hBBB
10   hABA   hBAB
12   hAAA   hBBB
13   hAAB   hBBA
14   hABA   hABA
15   hAAB   hBAB

The final output have eight columns group1.haplo1, goup1.haplo2, group2.haplo1, group2.haplo2, group3.haplo1, group4.haplo1, group4.haplo2.

How can I achieve this ?

Answer 1

Is this what you’re after? (specify the column numbers of the groups as elements of the list assigned to grps). You’ll need the reshape2 package installed. You could do something similar with rbind.fill() from the plyr package.

set.seed (14)
pool = sample (c("AA","AB", "BB"), 100, replace = T) 
mydf <- data.frame (M1= pool[1:10], M2= pool[11:20],
M3= pool[21:30], M4= pool[31:40],  M5= pool[41:50], 
  M6= pool[51:60],  M7= pool[61:70], M8 = pool[71:80], 
  M9 = pool[81:90],  M10 = pool[91:100])

library(hapassoc)

grps <- list(1:3, 4:5, 6:8, 9:10)
haplos <- lapply(grps, function(x) {
    out <- pre.hapassoc(mydf[, x], numSNPs=length(x), allelic=F, 
      verbose=F)$haploMat
    row.names(out) <- as.numeric(row.names(out))
    out
})
haplos <- lapply(haplos, t)
library(reshape2)
haplos <- melt(haplos,value.name='haplotype')
haplos <- dcast(haplos, Var2 ~ L1 + Var1, value.var='haplotype')

RESULT

haplos

   Var2 1_haplo1 1_haplo2 2_haplo1 2_haplo2 3_haplo1 3_haplo2 4_haplo1 4_haplo2
1     1     hABA     hABB      hBA      hBA     hAAA     hAAB      hAA      hAA
2     2     <NA>     <NA>      hAB      hAB     hAAB     hABB      hAA      hAA
3     3     hBAA     hAAB      hBA      hBB     hBBB     hBAA      hAA      hBA
4     4     hBBB     hBAA      hBA      hAB     <NA>     <NA>      hAB      hBB
5     5     <NA>     <NA>      hBB      hAA     hABB     hAAA      hAB      hBB
6     6     hABB     hBBB      hBA      hBB     hABA     hAAB      hBB      hBB
7     7     hBBB     hBBB      hAA      hAA     hBBB     hBAA      hAB      hBB
8     8     hBBB     hABA      hBA      hAB     <NA>     <NA>      hAA      hAA
9     9     <NA>     <NA>      hBB      hAA     hAAB     hAAB      hAA      hAB
10   10     hBBB     hBAA      hAA      hBA     hABB     hBBB      hAB      hAB
11   11     <NA>     <NA>      hBB      hBB     hBBA     hBBB     <NA>     <NA>
12   12     hBBB     hABA      hAB      hBB     hABA     hABB     <NA>     <NA>
13   13     <NA>     <NA>     <NA>     <NA>     hABB     hBAA     <NA>     <NA>
14   14     hABB     hBBB     <NA>     <NA>     <NA>     <NA>     <NA>     <NA>
15   15     <NA>     <NA>     <NA>     <NA>     hAAB     hBBA     <NA>     <NA>
16   16     hBAA     hABA     <NA>     <NA>     hAAA     hBBB     <NA>     <NA>