HPDplot, HPDpoints
Calculates and plots posterior means with 95% credible intervals for specified fixed effects (or their combination) for all genes. HPDpoints only adds graphs to an existing plot.
HPDpoints(model, factors, factors2 = NULL, ylimits = NULL, hpdtype = "w", inverse = F, jitter = 0, ...)
model |
The output of mcmc.qpcr function. |
factors |
A vector of names of fixed effects of interest; see details. |
factors2 |
A second vector of fixed effect names to be subtracted from the first; see details. |
ylimits |
Y-limits for the plot such as c(-3,6); autoscale by default. |
hpdtype |
Specify hpdtype="l" to plot the upper and lower 95% credible limits as a continuous dashed line across all genes. By default (hpdtype="w") the limits are plotted as whiskers around each point. |
inverse |
Plot the inverse of the result. |
jitter |
For hpdtype="w", shifts the plotted values and whiskers by the specified distance along the x axis (reasonable jitter values are 0.15 or -0.15, for example). |
... |
Various plot() options; such as col (color of lines and symbols), pch (type of symbol), main (plot title) etc. |
See details in HPDplot()
A graph added to a plot.
Mikhail V. Matz, UT Austin <matz@utexas.edu>
Matz MV, Wright RM, Scott JG (2013) No Control Genes Required: Bayesian Analysis of qRT-PCR Data. PLoS ONE 8(8): e71448. doi:10.1371/journal.pone.0071448
# loading Cq data and amplification efficiencies data(coral.stress) data(amp.eff) # extracting a subset of data cs.short=subset(coral.stress, timepoint=="one") genecolumns=c(5,6,16,17) # specifying columns corresponding to genes of interest conditions=c(1:4) # specifying columns containing factors # calculating molecule counts and reformatting: dd=cq2counts(data=cs.short,genecols=genecolumns, condcols=conditions,effic=amp.eff,Cq1=37) # fitting the model mm=mcmc.qpcr( fixed="condition", data=dd, controls=c("nd5","rpl11"), nitt=4000 # remove this line when analyzing real data! ) # plotting log2(fold change) in response to heat stress for all genes HPDplot(model=mm,factors="conditionheat",main="response to heat stress")
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