codeMarkers {statgenGWAS}

Code and impute markers

Description

codeMarkers codes markers in a gData object and optionally performs imputation of missing values as well.
The function performs the following steps:

1. replace strings in naStrings by NA.

2. remove genotypes with a fraction of missing values higher than nMissGeno.

3. remove SNPs with a fraction of missing values higher than nMiss.

4. recode SNPs to numerical values.

5. remove SNPs with a minor allele frequency lower than MAF.

6. optionally remove duplicate SNPs.

7. optionally impute missing values.

8. repeat steps 5. and 6. if missing values are imputed.

Usage

codeMarkers(
  gData,
  refAll = "minor",
  nMissGeno = 1,
  nMiss = 1,
  MAF = NULL,
  MAC = NULL,
  removeDuplicates = TRUE,
  keep = NULL,
  impute = TRUE,
  imputeType = c("random", "fixed", "beagle"),
  fixedValue = NULL,
  naStrings = NA,
  verbose = FALSE
)

Arguments

gData

An object of class gData containing at least markers.

refAll

A character string indicating the reference allele used when recoding markers.
If "minor", then the recoding is done using the minor allele as reference allele. Alternatively a single character can be supplied as a reference allele for the whole set of SNPs, or a character vector with a reference allele per SNP.

nMissGeno

A numerical value between 0 and 1. Genotypes with a fraction of missing values higher than nMissGeno will be removed. Genotypes with only missing values will always be removed.

nMiss

A numerical value between 0 and 1. SNPs with a fraction of missing values higher than nMiss will be removed. SNPs with only missing values will always be removed.

MAF

A numerical value between 0 and 1. SNPs with a Minor Allele Frequency (MAF) below this value will be removed. Only one of MAF and MAC may be specified.

MAC

A numerical value. SNPs with Minor Allele Count (MAC) below this value will be removed. Only one of MAF and MAC may be specified.

removeDuplicates

Should duplicate SNPs be removed?

keep

A vector of SNPs that should never be removed in the whole process.

impute

Should imputation of missing values be done?

imputeType

A character string indicating what kind of imputation of values should be done.

• fixed - missing values will be replaced by a given fixed value.

• random - missing values will be replaced by a random value calculated using allele frequencies per SNP.

• beagle - missing values will be imputed using beagle software, version 5.2. Beagle only accepts integers as map positions. If you use this option, please cite the original papers in your publication (see references).

fixedValue

A numerical value used for replacing missing values in case inputType is fixed.

naStrings

A character vector of strings to be treated as NA.

verbose

Should a summary of the performed steps be printed?

Value

A copy of the input gData object with markers replaced by coded and imputed markers.

References

S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097. doi:10.1086/521987

Examples

## Create markers
markers <- matrix(c(
"AA",   "AB",   "AA",   "BB",   "BA",   "AB",   "AA",   "AA",   NA,  "AA",
"AA",   "AA",   "BB",   "BB",   "AA",   "AA",   "BB",   "AA",   NA,  "AA",
"AA",   "BA",   "AB",   "BB",   "AB",   "AB",   "AA",   "BB",   NA,  "AA",
"AA",   "AA",   "BB",   "BB",   "AA",   "AA",   "AA",   "AA",   NA,  "AA",
"AA",   "AA",   "BB",   "BB",   "AA",   "BB",   "BB",   "BB",  "AB", "AA",
"AA",   "AA",   "BB",   "BB",   "AA",    NA,    "BB",   "AA",   NA,  "AA",
"AB",   "AB",   "BB",   "BB",   "BB",   "AA",   "BB",   "BB",   NA,  "AB",
"AA",   "AA",    NA,    "BB",    NA,    "AA",   "AA",   "AA",  "AA", "AA",
"AA",    NA,     NA,    "BB",   "BB",   "BB",   "BB",   "BB",  "AA", "AA",
"AA",    NA,    "AA",   "BB",   "BB",   "BB",   "AA",   "AA",   NA,  "AA"),
ncol = 10, byrow = TRUE, dimnames = list(paste0("IND", 1:10),
paste0("SNP", 1:10)))

## create object of class 'gData'.
gData <- createGData(geno = markers)

## Code markers by minor allele, no imputation.
gDataCoded1 <- codeMarkers(gData = gData, impute = FALSE)

## Code markers by reference alleles, impute missings by fixed value.
gDataCoded2 <- codeMarkers(gData = gData,
                           refAll = rep(x = c("A", "B"), times =  5),
                           impute = TRUE, imputeType = "fixed",
                           fixedValue = 1)

## Code markers by minor allele, impute by random value.
gDataCoded3 <- codeMarkers(gData = gData, impute = TRUE,
                           imputeType = "random")