knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
We computed the analysis in this publication in a series of steps, each dependent on the next, linked together via the traditional development tool gnu make
. We fit some example serological data sets (Morrison 2010 and L'Azou 2016, both collected from published studies and available as part of this package),
and then use those fits to simulate populations.
All of the scripts mentioned in this vignette are included in the inst/extdata
of this package, and can be located wherever your R packages are installed, or accessed via the build.project
tool to make a skeleton, or by using list.files(system.file("extdata/pub", package="denvax"), pattern=".R", full.names = T)
to get the paths.
The skeleton includes a 'Makefile' that defines a general set of dependencies, as well as the specific steps used to generate the figures in the published manuscript. The simple.R
script demonstrates a simple start-to-finish analysis (using the Morrison 2010 data included in the package).
In either approach, the steps are:
fit.R
script from build.project
in Rstudio, write your own script with the denvax::serofit
function, or use make with the target %-fit.json
in Makefile).synthesize.R
script, the denvax::synthetic.pop
function, or the target %-lh.rds
in Makefile)digest.R
script, the denvax::npxa
function, or the target %-npxa.rds
in Makefile)denvax::ROIcoeffs
function)denvax::ROI
function).Within the pub/
directory, we have another makefile and scripts which cover the specific analyses used in the publication.
Any scripts or data that you put into this service are public.
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