imputeData: Impute the missing values of Data.

In GaoLabXDU/CEPICS: CEPICS: a comparison and evaluation platform for integration methods in cancer subtyping

Description

Using different methods to impute the missing values of the data. CEPICS provides three imputation methods.

Usage

imputeData(data, method = "knn", k = 10, trans_zero_to_NA = FALSE)

Arguments

data	The data matrix needs to be imputed.
method	Choose from "knn", "mean", and "median". "knn": using K nearest neighbors methods to impute the missing value. "mean": using the mean value of each feature to impute the missing value. "median": using the median value of each feature to impute the missing value.
k	An integer value which means the number of the nearest neighbors when using KNN method to impute missing values.
trans_zero_to_NA	A logical value. If TRUE, all zeros in the data will be converted to NA.

References

Troyanskaya,O. et al. (2001) Missing value estimation methods for DNA microarrays. Bioinformatics, 17, 520-525.

Examples

data(COAD_Methy)
COAD_Methy <- imputeData(COAD_Methy, method = 'mean')

GaoLabXDU/CEPICS documentation built on June 9, 2020, 2:31 a.m.