R: Imputation of peptides having no value in a biological...

impute.pa {imp4p} | R Documentation

## Imputation of peptides having no value in a biological condition (present in a condition / absent in another).

### Description

This function imputes missing values by small values.

### Usage

    impute.pa(tab, conditions, q.min = 0.025, q.norm = 3, eps = 0,
    distribution = "unif", param1 = 3, param2 = 1, R.q.min=1)

### 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.
`q.min` | A quantile value of the observed values allowing defining the maximal value which can be generated. This maximal value is defined by the quantile `q.min` of the observed values distribution minus `eps`. Default is 0.025 (the maximal value is the 2.5 percentile of observed values minus `eps`).
`q.norm` | A quantile value of a normal distribution allowing defining the minimal value which can be generated. Default is 3 (the minimal value is the maximal value minus qn*median(sd(observed values)) where sd is the standard deviation of a row in a condition).
`eps` | A value allowing defining the maximal value which can be generated. This maximal value is defined by the quantile `q.min` of the observed values distribution minus `eps`. Default is 0.
`distribution` | Distribution used to generated missing values. You have the choice between "unif" for the uniform distribution, "beta" for the Beta distribution or "dirac" for the Dirac distribution. Default is "unif".
`param1` | Parameter `shape1` of the Beta distribution.
`param2` | Parameter `shape2` of the Beta distribution.
`R.q.min` | Parameter used for the Dirac distribution. In this case, all the missing values are imputed by a single value which is equal to `R.q.min*quantile(tab[,j], probs=q.min, na.rm=T)`. Default is 1 : the imputed value is the `qmin` quantile of observed values.

### Details

This function replaces the missing values in a column by random draws from a specified distribution. The value of `eps` can be interpreted as a minimal fold-change value above which the present/absent peptides appear.

### Value

A list composed of :

- `tab.imp` : the input matrix `tab` with imputed values instead of missing values.

- `para` : the parameters of the distribution which has been used to impute.

### 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 small values
    data.small.val=impute.pa(res.sim$dat.obs,res.sim$conditions);

[Package imp4p version 1.1 Index]