plotobservedsnps: Plot expected frequency of polymorphic sites in a model deep...
In seedy: Simulation of Evolutionary and Epidemiological Dynamics

Description Usage Arguments Details Value Author(s) Examples

Given an average depth of coverage and per base sequencing error rate, estimate the read frequency of most common polymorphic sites.

1 2	plotobservedsnps(data, timepoint=1, coverage=50, error=0.001, iterations=100, maxsnp=50, legend=TRUE, ylim=c(0,1.5*coverage), ...)

`data`	Full sequence data generated from the `simulatepopulation` function.
`timepoint`	Which sampling time should be used.
`coverage`	Coverage depth.
`error`	Sequencing erorr rate per base.
`iterations`	Number of iterations to generate confidence bounds.
`maxsnp`	Number of polymorphic sites to show.
`legend`	Should a legend be plotted?
`ylim`	Bounds of y axis.
`...`	Additional arguments to be passed to `plot`.

Plots the expected number of reads containing the most frequent polymorphisms, with a 95% confidence interval, derived from repeated random draws. Additionally shows the frequency of false positive observations arising through sequencing error.

Returns an iterations x maxsnp matrix. Each column represents a polymorphic site, and each row one iteration. Each entry provides the number of reads containing the polymorphism in a given iteration. Columns are ordered by frequency.

T. D. Read (tread@emory.edu)

data(deepseq)

# At the 25th time point
plotobservedsnps(data=deepseq, timepoint=25, xaxt="n", xlab="Ranked polymorphic sites", 
      ylab="Reads", yaxs="i", las=1)
# At the 50th time point
plotobservedsnps(data=deepseq, timepoint=50, xaxt="n", xlab="Ranked polymorphic sites", 
      ylab="Reads", yaxs="i", las=1)