makeGenotypes: Convert columns in a dataframe to genotypes or haplotypes

In kindlychung/genetics: Population Genetics

Description

Convert columns in a dataframe to genotypes or haplotypes.

Usage

makeGenotypes(data, convert, sep = "/", tol = 0.5, ..., method=as.genotype)
makeHaplotypes(data, convert, sep = "/", tol = 0.9, ...)

Arguments

data	Dataframe containing columns to be converted
convert	Vector or list of pairs specifying which columns contain genotype/haplotype data. See below for details.
sep	Genotype separator
tol	See below.
...	Optional arguments to as.genotype function
method	Function used to perform the conversion.

Details

The functions makeGenotypes and makeHaplotypes allow the conversion of all of the genetic variables in a dataset to genotypes or haplotypes in a single step.

The parameter convert may be missing, a vector of column names, indexes or true/false indictators, or a list of column name or index pairs.

When the argument convert is not provided, the function will look for columns where at least tol*100% of the records contain the separator character sep ('/' by default). These columns will then be assumed to contain both of the genotype/haplotype alleles and will be converted in-place to genotype variables.

When the argument convert is a vector of column names, indexes or true/false indictators, the corresponding columns will be assumed to contain both of the genotype/haplotype alleles and will be converted in-place to genotype variables.

When the argument convert is a list containing column name or index pairs, the two elements of each pair will be assumed to contain the individual alleles of a genotype/haplotype. The first column specified in each pair will be replaced with the new genotype/haplotype variable named name1 + sep + name2. The second column will be removed.

Note that the method argument may be used to supply a non-standard conversion function, such as as.genotype.allele.count, which converts from [0,1,2] to ['A/A','A/B','A/C'] (or the specified allele names). See the example below.

Value

Dataframe containing converted genotype/haplotype variables. All other variables will be unchanged.

Author(s)

Gregory R. Warnes [e-mail]

See Also

genotype

Examples

## Not run: 
# common case
data <- read.csv(file="genotype_data.csv")
data <- makeGenotypes(data)

## End(Not run)

# Create a test data set where there are several genotypes in columns
# of the form "A/T".
test1 <- data.frame(Tmt=sample(c("Control","Trt1","Trt2"),20, replace=TRUE),
                G1=sample(c("A/T","T/T","T/A",NA),20, replace=TRUE),
                N1=rnorm(20),
                I1=sample(1:100,20,replace=TRUE),
                G2=paste(sample(c("134","138","140","142","146"),20,
                                replace=TRUE),
                         sample(c("134","138","140","142","146"),20,
                                replace=TRUE),
                         sep=" / "),
                G3=sample(c("A /T","T /T","T /A"),20, replace=TRUE),
                comment=sample(c("Possible Bad Data/Lab Error",""),20,
                               rep=TRUE)
                )
test1

# now automatically convert genotype columns
geno1 <- makeGenotypes(test1)
geno1

# Create a test data set where there are several haplotypes with alleles
# in adjacent columns.
test2 <- data.frame(Tmt=sample(c("Control","Trt1","Trt2"),20, replace=TRUE),
                    G1.1=sample(c("A","T",NA),20, replace=TRUE),
                    G1.2=sample(c("A","T",NA),20, replace=TRUE),
                    N1=rnorm(20),
                    I1=sample(1:100,20,replace=TRUE),
                    G2.1=sample(c("134","138","140","142","146"),20,
                                replace=TRUE),
                    G2.2=sample(c("134","138","140","142","146"),20,
                                replace=TRUE),
                    G3.1=sample(c("A ","T ","T "),20, replace=TRUE),
                    G3.2=sample(c("A ","T ","T "),20, replace=TRUE),
                    comment=sample(c("Possible Bad Data/Lab Error",""),20,
                                   rep=TRUE)
                   ) 
test2

# specifly the locations of the columns to be paired for haplotypes
makeHaplotypes(test2, convert=list(c("G1.1","G1.2"),6:7,8:9))

# Create a test data set where the data is coded as numeric allele
# counts (0-2).
test3 <- data.frame(Tmt=sample(c("Control","Trt1","Trt2"),20, replace=TRUE),
                    G1=sample(c(0:2,NA),20, replace=TRUE),
                    N1=rnorm(20),
                    I1=sample(1:100,20,replace=TRUE),
                    G2=sample(0:2,20, replace=TRUE),
                    comment=sample(c("Possible Bad Data/Lab Error",""),20,
                                   rep=TRUE)
                   ) 
test3

# specifly the locations of the columns, and a non-standard conversion
makeGenotypes(test3, convert=c('G1','G2'), method=as.genotype.allele.count)

kindlychung/genetics documentation built on May 20, 2019, 9:58 a.m.