Description Details Author(s) Examples
A package of functions to simulate, visualize and assess epidemiological and pathogen genomic sample data collected during an outbreak.
Package: | seedy |
Type: | Package |
Version: | 1.3 |
Date: | 2015-11-06 |
License: | GPL-3 |
Colin Worby (cworby@hsph.harvard.edu)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | # Load within host data
data(withinhost)
# Calculate genetic distance matrix
Gmat <- gd(withinhost$obs.strain, withinhost$libr, withinhost$nuc,
withinhost$librstrains)
# Set colors
colvec <- rainbow(1200)[1:1000] # Color palette
coltext <- rep("black", length(colvec)) # Corresponding text colors
coltext[680:970] <- "white" # White text for darker background colours
# Plot distance matrix
plotdistmat(Gmat, colvec, coltext, pos="bottomleft", labels=NULL, numbers=TRUE)
# Load outbreak data
data(outbreak)
sampledata <- outbreak$sampledata
epidata <- outbreak$epidata
# Calculate distance matrix for observed samples
distmat <- gd(sampledata[,3], outbreak$libr, outbreak$nuc, outbreak$librstrains)
# Now pick colors for sampled isolates
refnode <- 1 # Compare distance to which isolate?
colv <- NULL # Vector of colors for samples
maxD <- max(distmat[,refnode])
for (i in 1:nrow(sampledata)) {
colv <- c(colv,
colvec[floor((length(colvec)-1)*(distmat[refnode,i])/maxD)+1])
}
plotoutbreak(epidata, sampledata, col=colv, stack=TRUE, arr.len=0.1,
blockheight=0.5, hspace=500, label.pos="left", block.col="grey",
jitter=0.004, xlab="Time", pch=1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.