SmCCNet (version 2.0.3)

dataPreprocess: preprocess a omics dataset before running omics SmCCNet

Description

Data preprocess pipeline to: (1) filter by coefficient of variation (cv), (2) center or scale data and (3) adjust for clinical covariates.

Usage

dataPreprocess(
  X,
  covariates = NULL,
  is_cv = FALSE,
  cv_quantile = 0,
  center = TRUE,
  scale = TRUE
)

Value

Processed omics data with the size of nxp.

Arguments

X

dataframe with the size of \(n\) by \(p\), where \(n\) is the sample size and \(p\) is the feature size.

covariates

dataframe with covariates to be adjusted for.

is_cv

Whether to use coefficient of variation filter (small cv filter out).

cv_quantile

CV filtering quantile.

center

Whether to center the dataset X.

scale

Whether to scale the dataset X.

Examples

X1 <- as.data.frame(matrix(rnorm(600, 0, 1), nrow = 60))
covar <- as.data.frame(matrix(rnorm(120, 0, 1), nrow = 60))
processed_data <- dataPreprocess(X = X1, covariates = covar, is_cv = TRUE, 
cv_quantile = 0.5, center = TRUE, scale = TRUE)