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Imputation by Bayesian principal components analysis

impute.pca_bayes.Rd

Apply imputation to the data by Bayesian principal components analysis (Oba et al. 2003) .

Usage

impute.pca_bayes(dataSet, nPcs = NULL, maxSteps = 100)

Arguments

dataSet

A data frame containing the data signals.

nPcs

An integer specifying the number of principal components to calculate. The default is set to the minimum between the number of samples and the number of proteins.

maxSteps

An integer (default = 100) specifying the maximum number of estimation steps.

Value

The imputed data.

References

Oba S, Sato M, Takemasa I, Monden M, Matsubara K, Ishii S (2003). “A Bayesian Missing Value Estimation Method for Gene Expression Profile Data.” Bioinformatics, 19(16), 2088–2096. doi:10.1093/bioinformatics/btg287 .