quest: Construct and apply the QuEST model with your own data

In QuESTr: Constructing Quantitative Environment Sensor using Transcriptomes

Construct and apply the QuEST model with your own data

Description

Construct and apply the QuEST model with your own data

Usage

quest(x, y, newx = x, method = "linear", lower.thr = 0, n.gene = 0)

Arguments

x	A data matrix (row: samples, col: genes).
y	A vector of an environment in which the samples were collected.
newx	A data matrix (row: samples, col: genes).
method	A string to specify the method of regression for calculating R-squared values. "linear" (default), "quadratic" or "cubic" regression model can be specified.
lower.thr	The lower threshold of R-squared value to be used in QuEST model (default: 0).
n.gene	The number of candidate genes to be used in QuEST 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 <- q.clean(Pinus$train)
test <- Pinus$test
test <- test[, colnames(train)]
target <- Pinus$target
cor(target, quest(train, target, newx = test, method = "cubic"))

QuESTr documentation built on March 18, 2022, 5:09 p.m.