transmission: Outbreak data

In seedy: Simulation of Evolutionary and Epidemiological Dynamics

Description

Simulated outbreak data and genomic samples. An SIR outbreak was simulated with an infective individual entering a population of thirty susceptibles. A single genome was isolated from each individual during their infectious period.

Usage

transmission

Format

Consists of epidemiological data and genomic sample data.

Examples

data(transmission)
W <- transmission

ID <- unique(W$sampledata[,1])
GD <- gd(W$sampledata[,3], W$libr, W$nuc, W$librstrains)

sample.times <- W$sampledata[,2]
inf.times <- numeric(length(ID))
rec.times <- numeric(length(ID))
truesource <- numeric(length(ID))
for (i in 1:length(ID)) {
  inf.times[i] <- W$epidata[which(W$epidata[,1]==ID[i]),2]
  rec.times[i] <- W$epidata[which(W$epidata[,1]==ID[i]),3]
  truesource[i] <- W$epidata[which(W$epidata[,1]==ID[i]),4]
}

colvec <- rainbow(1200)[1:1000] # Color palette
refnode <- 1 # Compare distance to which isolate?
colv <- NULL # Vector of colors for samples
maxD <- max(GD[,refnode])
for (i in 1:length(ID)) {
  colv <- c(colv, colvec[floor((length(colvec)-1)*(GD[refnode,i])/maxD)+1])
}

plotoutbreak(W$epidata, W$sampledata, col=colv, pch=16)
  K <- transroutes(ID=ID, GD=GD, sample.times=sample.times, inf.times=inf.times, 
                   rec.times=rec.times, mut.rate=0.01, eq.size=5000, 
                   bottle.size=1, p.level=0.95, summary=TRUE)
truesource
K$maxpostsource
		

seedy documentation built on May 29, 2017, 10:58 a.m.