q.rank: Visualize R-squared value distribution in gene-environment...

In takakoizumi/QuEST: Constructing Quantitative Environment Sensor using Transcriptomes

Description

Visualize R-squared value distribution in gene-environment interaction

Usage

q.rank(
  x,
  y,
  method = "linear",
  lower.thr = 0,
  n.gene = ncol(x),
  upper.xlim = ncol(x)
)

Arguments

x	A data matrix (row: samples, col: genes).
y	A vector of an environment in which the samples were collected.
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 included in QuEST model (default: 0).
n.gene	The number of genes to be included in QuEST model (default: ncol(x)).
upper.xlim	The upper limitation of x axis (i.e., the number of genes) in the resulted figure (default: ncol(x)).

Value

A rank order plot

Author(s)

Takahiko Koizumi

Examples

data(Pinus)
train <- q.clean(Pinus$train)
target <- Pinus$target
train <- q.sort(train, target)
q.rank(train, target, lower.thr = 0.5)

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