arrayAppend: Append two arrays by adding new data to top array

Description

arrayAppend is a function to append two arrays by adding new data to array whose name is placed in the first argument of the function.

Usage

arrayAppend(topA, bottomA, missingVal = 5)

Arguments

topA

Old data.

bottomA

New data.

missingVal

Value to use for missing SNPs in new data, default = 5.

Value

An object of class matrix with ‘number of rows = number of individuals in both matrices, topA and bottomA’ and ‘number of columns = number of SNPs as listed in old data’.

Details

Two matrices created by the function, toArray, can be appended together using arrayAppend. Appending is more efficient after recoding each of the two matrices by using snpRecode. The first input argument topA holds old data, i.e., data to hold on to its SNP list. The second argument, bottomA, holds new data that needs to be fit to old SNP list. Therefore, missing SNPs in new data will be created anew but will be given the value of ‘missingVal’, with a default of 5. This also assumes that you will be imputing these missing values later on.

arrayAppend goes by the SNP list of the old data in the first input argument, so if the new data matrix has more SNPs, they will be ignored. If you need to consider the extra SNPs, switch the order of the input matrices of the function.

Examples

Run this code

# NOT RUN {
ga.old <- matrix(sample(c(0,1,2,5), size = 30, repl = TRUE), nrow=3, ncol=10,
  dimnames = list(paste("Individual", 1:3, sep="."), paste("SNP", 1:10, sep=".")))

ga <- matrix(sample(c(0,1,2,5), size = 24, repl = TRUE), nrow=3, ncol=8,
dimnames = list(paste("Individual", 4:6, sep="."), paste("SNP", 1:8, sep=".")))

arrayAppend(ga.old, ga)
arrayAppend(ga.old, ga)

#
#             SNP.1 SNP.2 SNP.3 SNP.4 SNP.5 SNP.6 SNP.7 SNP.8 SNP.9 SNP.10
#Individual.1     5     5     0     1     2     1     2     5     1      2
#Individual.2     2     2     2     0     1     1     1     1     2      0
#Individual.3     1     1     5     0     5     5     0     5     5      5
#Individual.4     1     2     1     1     0     2     0     0     5      5
#Individual.5     2     1     2     1     0     1     2     1     5      5
#Individual.6     0     2     0     2     5     0     1     1     5      5
#
#Note that SNP.9 and SNP.10 were added to new data but were assigned the default
#code, 5, for missing values. You should impute all missing values afterwards.
#

#If the order of input matrices is switched, the extra SNPs in the second argument
#will be ignored. This function goes by the SNP list of the first arguement.

arrayAppend(ga, ga.old)

#             SNP.1 SNP.2 SNP.3 SNP.4 SNP.5 SNP.6 SNP.7 SNP.8
#Individual.4     1     2     1     1     0     2     0     0
#Individual.5     2     1     2     1     0     1     2     1
#Individual.6     0     2     0     2     5     0     1     1
#Individual.1     5     5     0     1     2     1     2     5
#Individual.2     2     2     2     0     1     1     1     1
#Individual.3     1     1     5     0     5     5     0     5

# }