rcq: Simulate Cq data

In edpcr: Performs Extended Digital PCR Analysis

Description

Simulates Cq data by simulating molecule growth and calculating Cq values through simple algorithm.

Usage

rcq(E=.95,E1=.95,mu=1.5,disp=1.2,N=10^4,nx=70,ny=11,h=.1,A=10^-10,c.mean=NULL,trendx=NULL,trendy=NULL,incxy=TRUE)

Arguments

E	efficiency (probability).
E1	cycle 1 efficiency (probability).
mu	average number of molecules per partition (positive).
disp	dispersion parameter ν (positive).
N	number of Cq trials (each results in either a Cq value or contributes to the count of negative partitions).
nx, ny	numbers of columns and rows.
h	threshold value.
A	fluorescence per molecule.
c.mean	mean Cq (alternative to specifying A).
trendx,trendy	x- and y-trends added to Cq data.
incxy	if TRUE then output includes x- and y-locations.

Details

Simulates molecule growth where each molecule amplifies with probability E (E_1 in cycle 1). Cq values are calculated based on exponential growth between the cycles immediately before and after the threshold is crossed.

Value

If incxy is TRUE a matrix including Cq values, x- and y-locations, otherwise a vector of Cq values. For negative partitions, Cq values are given as NA.

Author(s)

Philip Wilson

Examples

sim1<-rcq(.95,.65,N=1000,c.mean=25.5)
sim2<-rcq(.9,.9,nx=70,ny=11,c.mean=25.5,trendx=10^-3,trendy=10^-4)

edpcr documentation built on May 2, 2019, 5:22 p.m.