Imputation of peptides with a random value.
For each row (peptide), this function imputes missing values by random values following a Gaussian distribution.
impute.rand(tab, conditions)
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. |
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).
The input matrix tab with imputed values instead of missing values.
Quentin Giai Gianetto <quentin2g@yahoo.fr>
#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);
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