rpt_diff: Likelihood-based Tests for Detecting Differential Circadian...

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

Likelihood-based Tests for Detecting Differential Circadian Pattern with Repeated Measurement

Description

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

Usage

rpt_diff(tt1, yy1, tt2, yy2, id1, id2, group, period = 24, method = "LR")

Arguments

tt1	Time vector of condition 1.
yy1	Expression vector of condition 1.
tt2	Time vector of condition 2.
yy2	Expression vector of condition 2.
id1	Subject ID numbers in group 1.
id2	Subject ID numbers in group 2.
group	Group indicator of all subjects.
period	Period of the since curve. Default is 24.
method	Test used to detect differential circadian pattern. It can be chosen either "LR" or "F". Default is LR.

Details

Test differential rhythmicity of circadian curve fitting using random intercept linear mixed model and likelihood-based tests.

Value

A list, see details below.

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.
A1	Amplitude for group 1.
A2	Amplitude for group 2.
phi1	Phase for group 1.
phi2	Phase for group 2.
basal1	Basal level for group 1.
basal2	Basal level for group 2.
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)
n1 <- 12
n2 <- 12
m1 <- 10
m2 <- 10
id1 <- rep(1:n1,each=m1)
id2 <- rep((1+n1):(n1+n2),each=m2)
rho <- 0.2
offset1 <- runif(1,0,3)
offset2 <- runif(1,2,5)
amp1 <- 1
amp2 <- 2
phase1 <- 3
phase2 <- 6
sigmaMat1 <- ifelse(diag(m1)==1,1,rho)
sigmaMat2 <- ifelse(diag(m2)==1,1,rho)
t1 <- runif(m1,0,24)
tt1 <- rep(t1,n1)
yy1 <- as.vector(t(mvrnorm(n1,amp1*sin(2*pi/24*(phase1+t1))+offset1,sigmaMat1)))
t2 <- runif(m2,0,24)
tt2 <- rep(t2,n2)
yy2 <- as.vector(t(mvrnorm(n2,amp2*sin(2*pi/24*(phase2+t2))+offset2,sigmaMat2)))
group <- c(rep("group1",n1*m1),rep("group2",n2*m2))
rpt_diff(tt1,yy1,tt2,yy2,id1,id2,group)


Example 2

set.seed(32611)
n1 <- 12
n2 <- 12
m1 <- 10
m2 <- 10
id1 <- rep(1:n1,each=m1)
id2 <- rep((1+n1):(n1+n2),each=m2)
rho <- 0.2
offset1 <- offset2 <- runif(1,0,3)
sigmaMat1 <- ifelse(diag(m1)==1,1,rho)
sigmaMat2 <- ifelse(diag(m2)==1,1,rho)
t1 <- runif(m1,0,24)
tt1 <- rep(t1,n1)
yy1 <- as.vector(t(mvrnorm(n1,rep(offset1,m1),sigmaMat1)))
t2 <- runif(m2,0,24)
tt2 <- rep(t2,n2)
yy2 <- as.vector(t(mvrnorm(n2,rep(offset2,m2),sigmaMat2)))
group <- c(rep("group1",n1*m1),rep("group2",n2*m2))
rpt_diff(tt1,yy1,tt2,yy2,id1,id2,group)

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