R/data.R

In outbreaker: Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data

#' Toy outbreak dataset used to illustrate outbreaker
#' 
#' This toy outbreak dataset was simulated using \code{\link{simOutbreak}}.
#' This dataset is a list containing the following components: \itemize{ \item
#' dat: the data, output of simOutbreak; see \code{dat$call} for the actual
#' command line that was used.  \item w: the generation time distribution.
#' \item collecDates: simulated collection dates dates.  \item res: the results
#' of \code{outbreaker.parallel}; see \code{res$call} for the actual command
#' line that was used.  }
#' 
#' 
#' @name simulated outbreak dataset
#' @aliases fakeOutbreak
#' @docType data
#' @author Thibaut Jombart \email{t.jombart@@imperial.ac.uk}
#' @keywords datasets
#' @examples
#' 
#' \dontrun{
#' ## COMMAND LINES TO GENERATE SIMILAR DATA ##
#' w <- c(0, 0.5, 1, 0.75)
#' ## note: this works only if outbreak has at least 30 case
#' dat <- simOutbreak(R0 = 2, infec.curve = w, n.hosts = 100)[1:30]
#' collecDates <- dat$onset + sample(0:3, size=30, replace=TRUE, prob=w)
#' }
#' 
#' ## EXAMPLE USING TOYOUTBREAK ##
#' ## LOAD DATA, SET RANDOM SEED
#' data(fakeOutbreak)
#' attach(fakeOutbreak)
#' 
#' ## VISUALIZE DYNAMICS
#' matplot(dat$dynam, type="o", pch=20, lty=1,
#'    main="Outbreak dynamics", xlim=c(0,28))
#' legend("topright", legend=c("S","I","R"), lty=1, col=1:3)
#' 
#' ## VISUALIZE TRANSMISSION TREE
#' plot(dat, annot="dist", main="Data - transmission tree")
#' mtext(side=3, "arrow annotations are numbers of mutations")
#' 
#' 
#' \dontrun{
#' ## RUN OUTBREAKER - PARALLEL VERSION
#' ## (takes < 1 min))
#' set.seed(1)
#' res <-  outbreaker.parallel(n.runs=4, dna=dat$dna,
#'    dates=collecDates,w.dens=w, n.iter=5e4)
#' }
#' 
#' 
#' ## ASSESS CONVERGENCE OF CHAINS
#' plotChains(res)
#' plotChains(res, burnin=2e4)
#' 
#' ## REPRESENT POSTERIOR ANCESTRIES
#' transGraph(res, annot="", main="Posterior ancestries", thres=.01)
#' 
#' ## GET CONSENSUS ANCESTRIES
#' tre <- get.tTree(res)
#' plot(tre, annot="", main="Consensus ancestries")
#' 
#' ## SHOW DISCREPANCIES
#' col <- rep("lightgrey", 30)
#' col[which(dat$ances != tre$ances)] <- "pink"
#' plot(tre, annot="", vertex.color=col, main="Consensus ancestries")
#' mtext(side=3, text="cases with erroneous ancestries in pink")
#' 
#' ## GET EFFECTIVE REPRODUCTION OVER TIME
#' get.Rt(res)
#' 
#' ## GET INDIVIDUAL EFFECTIVE REPRODUCTION
#' head(get.R(res))
#' boxplot(get.R(res), col="grey", xlab="Case",
#'         ylab="Effective reproduction number")
#' 
#' ## GET MUTATION RATE PER TIME UNIT
#' ## per genome
#' head(get.mu(res))
#' 
#' ## per nucleotide
#' mu <- get.mu(res, genome.size=1e4)
#' head(mu)
#' 
#' summary(mu)
#' hist(mu, border="lightgrey", col="grey", xlab="Mutation per day and nucleotide",
#'      main="Posterior distribution of mutation rate")
#' 
#' detach(fakeOutbreak)
#' 
#' 
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