select_features: Selection of important features

In agapow/subtypr: Robust and Validated Patient Subtyping for Precision Medicine

Description

The parameters for each methods:

Usage

select_features(data, method = c("variance", "pca", "mad"), ...)

Arguments

data	a feature matrix, rows are samples and columns are features
method	"variance", "pca",
...	args to be passed to the selected method: "variance": cutoff: Minimum variance to be kept. "pca": min_pve: Minimum of percentage of variance explained by the selected principal components. scale: A logical value indicating wether the data is normalized before PCA. "mad": cutoff: Minimum MAD to be kept.

Details

• "variance": cutoff: Minimum variance to be kept.

  • "pca": min_pve: Minimum of percentage of variance explained by the selected principal components.

  • "mad": cutoff: Minimum MAD to be kept.

Value

data with only selected features or principal components.

agapow/subtypr documentation built on May 5, 2019, 1:33 a.m.