Imputation by Bayesian principal components analysis — impute.pca

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

Usage

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

Arguments

dataSet: The 2d dataset of experimental values.
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

An imputed 2d dataframe.

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 .