R: Imputation of peptides with a random value.

impute.rand {imp4p} | R Documentation

## Imputation of peptides with a random value.

### Description

For each row (peptide), this function imputes missing values by random values following a Gaussian distribution.

### Usage

    impute.rand(tab, conditions)

### Arguments

`tab` | A data matrix containing numeric and missing values. Each column of this matrix is assumed to correspond to an experimental sample, and each row to an identified peptide.
`conditions` | A vector of factors indicating the biological condition to which each column (experimental sample) belongs.

### Details

For each row (peptide), this function imputes missing values by random values following a Gaussian distribution centered on the mean of the observed values in the condition for the specific peptide and with a standard deviation equal to the first quartile of the distribution of the standard deviation the values observed for all the peptides. Rows with only missing values in a condition are not imputed (the `impute.pa` function can be used for this purpose).

### Value

The input matrix `tab` with imputed values instead of missing values.

### Author(s)

Quentin Giai Gianetto <quentin2g@yahoo.fr>

### Examples

    #Simulating data
    res.sim=sim.data(nb.pept=2000,nb.miss=600);

    #Imputation of the simulated data set with random values
    data.rand=impute.rand(res.sim$dat.obs,res.sim$conditions);

[Package imp4p version 1.1 Index]