q.opt: Estimate the optimal number of genes to construct QuEST model

In takakoizumi/QuEST: Constructing Quantitative Environment Sensor using Transcriptomes

Description

Estimate the optimal number of genes to construct QuEST model

Usage

q.opt(
  x,
  y,
  newx = NULL,
  newy = NULL,
  range = 5:50,
  method = "linear",
  rep = 1,
  signif = FALSE
)

Arguments

x	A data matrix (row: samples, col: genes).
y	A vector of an environment in which the samples were collected.
newx	(optional) A data matrix for validation. Columns of newx and x must be identical (default: NULL).
newy	(optional) A vector for validation (default: NULL).
range	A sequence of numbers of genes to be tested for MAE calculation (default: 5:50).
method	A string to specify the method of regression for calculating R-squared values. "linear" (default), "quadratic" or "cubic" regression model can be specified.
rep	The number of replications for each case set by range (default: 1).
signif	If TRUE, 95 will be illustrated on the resulting plot (default: FALSE).

Value

A sample-MAE curve

Author(s)

Takahiko Koizumi

Examples

data(Pinus)
train <- q.clean(Pinus$train)
target <- Pinus$target
q.opt(train, target)

takakoizumi/QuEST documentation built on Dec. 31, 2021, 12:06 a.m.