imputeSnpMatrix {GeneGeneInteR} | R Documentation

## Missing values handling for SnpMatrix object

### Description

`imputeSnpMatrix` is a generic wrapper of `snp.imputation` and `impute.snps` functions from `snpStats` package. This function mimics a Leave-One-Out process where missing SNPs are imputed for an individual based on a model trained on all other individuals.

### Usage

    imputeSnpMatrix(snpX, genes.info, on.rem = c("SNP", "ind", "none"),
      quiet = FALSE)

### Arguments

`snpX` | `snpMatrix` object of which SNPs are to be removed
`genes.info` | A `data.frame` with four columns named `Genenames`, `SNPnames`, `Position` and `Chromosome`. Each row describes a SNP and missing values are not allowed.
`on.rem` | (optional) a character string matching one of the following items: SNP, ind, none. Describes the action taken in case of remaining missing values. See details
`quiet` | (optional) a boolean describing wether or not progress bar should be displayed.

### Details

For the ith row in the `snpX` argument (i.e. the ith individual in the dataset), the following steps are performed:

- missing SNPs are detected for individual i

- rules are imputed for every missing SNPs using the whole dataset where individual i is removed

- SNPs are imputed for individual i

Although, such a process allows the imputation of a large number of missing SNPs, some missing values may remains. In that case, the user can specify the action to be done thanks to the `om.rem` arguments:

- `om.rem="none"`: leave the dataset as it is,

- `om.rem="SNP"`: remove all SNPs with remaining missing values,

- `om.rem="ind"`: remove all individuals with remaining missing values.

Removing all SNPs is often more parsimonious than removing individuals and allows to get a dataset without any missing values with minimum information-loss.

### Value

a list object with two named elements:

``snpX`` | a `SnpMatrix` object corresponding to input matrix with imputed values.
``genes.info`` | a data frame object corresponding to an updated version of input `genes.info` in case SNP had to be removed.

A warning is printed when SNPs or individuals are removed.

### See Also

`GGI` `snpMatrixScour`

### Examples

    ## Not run:
    ped <- system.file("extdata/example.ped", package="GeneGeneInteR")
    info <- system.file("extdata/example.info", package="GeneGeneInteR")
    posi <- system.file("extdata/example.txt", package="GeneGeneInteR")
    data.imported <- importFile(file=ped, snps=info, pos=posi, pos.sep="\t")

    ## Example 1 without SNPs filtering
    ## In this example, 9 SNPs were removed due to remaining missing values.
    imputed.snps.1 <- imputeSnpMatrix(data.imported$snpX, genes.info = data.imported$genes.info)

    ## Example 2 with SNPs filtering priori to the imputation
    ## Filtering of the data: SNPs with MAF < 0.05 or p.value for HWE < 1e-3 or SNPs with
    ## call.rate < 0.9 are removed.
    data.scour <- snpMatrixScour(snpX=dta$snpX,genes.info=dta$genes.info,min.maf=0.05,
                                  min.eq=1e-3,call.rate=0)

    ## End(Not run)

    ## Equivalent loading of data for example 2
    ## Imputation of the missing genotypes
    load(system.file("extdata/dataScour.Rdata", package="GeneGeneInteR"))

    data.imputed <- imputeSnpMatrix(data.scour$snpX, genes.info = data.scour$genes.info)

[Package GeneGeneInteR version 1.18.0 Index]