rpt_rhythmicity: Likelihood-based Test for Detecting Circadian Pattern with...

In RepeatedCircadian/RepeatedCircadian: An R package for circadian and differential circadian analysis with repeated measurement

Likelihood-based Test for Detecting Circadian Pattern with Repeated Measurement.

Description

Likelihood-based test for circadian pattern detection with repeated measurement.

Usage

rpt_rhythmicity(tt, yy, id, period = 24, method = "LR")

Arguments

tt	Time vector.
yy	Expression vector.
id	Subject ID numbers.
period	Period of the since curve. Default is 24.
method	Testing methods can be "LR" or "F". Default is "LR".

Details

Test the significance of circadian curve fitting using mixed model with random intercept and likelihood-based test.

Value

A list of test statistic and pvalue. Formula 1: yy = amp * sin(2π/period * (phase + tt)) + offset Formula 2: yy = A * sin(2π/period * tt) + B * cos(2*π/period * tt) + offset

stat	Test statistic.
pvalue	P-value from the test.
A	Amplitude estimate.
phi	Phase estimate.
basal	Basal level estimate.
sigma_0	Standard deviation for the fixed part of intercept.
sigma_alpha	Standard deviation for the random part of intercept.

Author(s)

Haocheng Ding, Zhiguang Huo

Examples

Example 1

set.seed(32611)
m <- 10
n <- 12
id <- rep(1:n,each=m)
rho <- 0.2
offset <- runif(1,0,3)
sigmaMat <- ifelse(diag(m)==1,1,rho)
tt <- rep(runif(m,0,24),n)
yy <- as.vector(t(mvrnorm(n,rep(offset,m),sigmaMat)))
rpt_rhythmicity(tt, yy, id, period=24, method="LR")

Example 2
set.seed(32611)
m <- 10
n <- 12
id <- rep(1:n,each=m)
rho <- 0.2
amp <- 1
phase <- 3
offset <- runif(1,0,3)
sigmaMat <- ifelse(diag(m)==1,1,rho)
t <- runif(m,0,24)
tt <- rep(t,n)
yy <- as.vector(t(mvrnorm(n,amp*sin(2*pi/24*(phase+t))+offset,sigmaMat)))
rpt_rhythmicity(tt, yy, id, period=24, method="LR")

RepeatedCircadian/RepeatedCircadian documentation built on Jan. 4, 2023, 11:11 p.m.