os.pred: Construct and apply the OmicSense model with your own data

In OmicSense: Biosensor Development using Omics Data

Construct and apply the OmicSense model with your own data

Description

Construct and apply the OmicSense model with your own data

Usage

os.pred(x, y, newx = x, method = "linear", thresh = 0, n.pred = 0)

Arguments

x	A data matrix (row: samples, col: predictors).
y	A vector of target value.
newx	A data matrix (row: samples, col: predictors).
method	A string to specify the regression function for calculating R-squared values. "linear" (default), "quadratic" or "cubic" function can be specified.
thresh	The lower threshold of R-squared value to be leaved in prediction model (default: 0).
n.pred	The number of candidate predictors to be leaved in prediction model (default: 30).

Value

A vector of the environment in which the samples of newx were collected

Author(s)

Takahiko Koizumi

Examples

data(Pinus)
train <- os.clean(Pinus$train)
test <- Pinus$test
test <- test[, colnames(train)]
target <- Pinus$target
cor(target, os.pred(train, target, newx = test, method = "cubic"))

OmicSense documentation built on Sept. 23, 2023, 1:06 a.m.