Nothing
## -----------------------------------------------------------------------------
# load the package
library(tbea)
# crossplot operates over files or dataframes. Let's create
# two dataframes to exemplified the desirable structure of input data
log1 <- data.frame(sample=seq(from=1, to=10000, by = 100),
node1=rnorm(n =100, mean=41, sd=0.5),
node2=rnorm(n =100, mean=50, sd=1),
node3=rnorm(n =100, mean=25, sd=1))
log2 <- data.frame(sample=seq(from=1, to=10000, by = 100),
node1=rnorm(n =100, mean=41, sd=0.2),
node2=rnorm(n =100, mean=50, sd=0.8),
node3=rnorm(n =100, mean=25, sd=0.5))
head(log1)
# run crossplot over nodes 1 and 2 using 'idx.cols' instead of 'pattern', and
# plot the mean instead of the median.
crossplot(log1, log2,
idx.cols=c(2,3),
stat="mean",
bar.lty=1,
bar.lwd=1,
identity.lty=2,
identity.lwd=1,
extra.space=0.5,
main="My first crossplot",
xlab="log 1",
ylab="log 2",
pch=19)
# now, load empirical data
data(cynodontidae.prior)
data(cynodontidae.posterior)
# as crossplot operates also over files, let's create temporal
# files for illustration
write.table(cynodontidae.prior, "prior.tsv",
row.names=FALSE, col.names=TRUE, sep="\t")
write.table(cynodontidae.posterior, "posterior.tsv",
row.names=FALSE, col.names=TRUE, sep="\t")
# crossplot
crossplot(log1="prior.tsv",
log2="posterior.tsv",
stat="median",
skip.char="#",
pattern="mrca.date",
bar.lty=1,
bar.lwd=2,
identity.lty=2,
identity.lwd=2,
main="Prior-posterior comparison\nCynodontidae",
xlab="Prior node age (Ma)",
ylab="Posterior node age (Ma)",
pch=20, cex=2, col="blue2")
## -----------------------------------------------------------------------------
# integrate the area under the curve
measureSimil(d1=cynodontidae.prior$mrca.date.backward.Hydrolycus.,
d2=cynodontidae.posterior$mrca.date.backward.Hydrolycus.,
ylim=c(0, 5),
xlab="Age (Ma)",
ylab="Density",
main="Similarity between prior and posterior\nof the node Hydrolycus")
# file cleanup
file.remove("prior.tsv")
file.remove("posterior.tsv")
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