convert {GeneticsBase} | R Documentation

## Efficienctly convert strings of characters into integer codes

### Description

Efficienctly convert strings of characters into integer codes.

### Usage

    convert(source, levels, byrow=FALSE, aslist=FALSE)

### Arguments

`source` | Vector of character strings
`levels` | Vector of characters used to determine levels
`byrow` | Boolean. If FALSE (the default), return a matrix with one column per string. If TRUE, return a matrix with one row per string.
`aslist` | Boolean, return matrix (FALSE) or list of vectors (TRUE).

### Details

This function efficiently converts character strings containing characters into vectors of integers. Its primary purpose is to allow translation of genotypes stored as character vectors, one character per genotype, to a factor-coded matrix. The equivalent code using `factor` is quite a bit slower, as shown by the last section of the example below.

The `levels` argument should be a vector of 1-character strings. This vector is used to determine the translation. The index of matching characters provides the returned integer values. Characters not present in `levels` will be converted to NA's.

### Value

If `aslist=TRUE`, the return value is a a list of vectors. Each vector will contain the translation of the corresponding input string.
If `aslist=FALSE (the default)`, the return value will be a matrix. `byrow` controls whether each string is converted into a a column (`byrow=FALSE`, the default) or row (`byrow=TRUE`).
When `byrow=FALSE`, each element of the `source` vector is converted to a column, and the number of rows will be the number of characters in the longest element of the `source` vector. Any shorter vectors will be padded with NA's.
When `byrow=TRUE` the matrix is created with one row per element of the `source` vector, etc.

### Note

Only of the first character of each element of `levels` is used. Any other characters will be ignored.

### Author(s)

Gregory R. Warnes warnes@bst.rochester.edu and Nitin Jain nitin.jain@pfizer.com

### See Also

`factor`, `as.factor`

### Examples

    ###
    # Toy Genetics Example
    ##
    # 'c' = 'homozygote common allele'
    # 'h' = 'heterozygone'
    # 'r' = 'homozygote rare allele'
    marker.data <- c( m1='cchchrcr', m2='chccccrr')
    marker.data

    convert(marker.data, c('c','h','r'))

    ###
    # simple test example
    ###
    source <- c(one='abcabcabc', two='abc','ggg',buckle='aaa',my='bbb',
                'shoe  '='bgb  ')
    levels <- c('a','b','c','d')

    convert(source,levels)
    convert(source,levels,aslist=TRUE)
    convert(source,levels,byrow=TRUE)

    ###
    # compare efficiency with equivalent code using 'factor'
    ###
    ## Not run:
    makestr <- function(n)
      paste(sample(letters, size=n, replace=T), sep='', collapse='')

    timeit <- function( expr )
      {
        start <- Sys.time()
        expr
        end <- Sys.time()
        return( as.numeric(end-start ))
      }

    # Step 1: create a large set of character strings
    x <- unlist(lapply(1:100000, function(x) makestr(1000)))

    # Step 2: Time convert  (~17 sec on Intel Xeon 3.0 GHz, 32 GB RAM)
    newtime <- timeit( yn <- convert2(x, letters) )
    newtime

    # old method  (~4.7 min on Intex Xeon 3.0 GHz, 32 GB RAM)
    oldmethod <- function(x)
      {
        yo <- factor(unlist(strsplit(x, split='')),levels=letters)
        attr(y1,'dim') <- c(nchar(x[1]), length(x))
        class(y1) <- 'matrix'
      }

    oldtime <- timeit( oldmethod(x) )
    oldtime

    # time difference
    oldtime - newtime
    ## End(Not run)

[Package GeneticsBase version 1.6.0 Index]