Description Usage Arguments Details Value Author(s) Examples
Generates a heatmap plot of the pooled data or one plot for each dataset.
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x |
a character, the name of a numerical vector |
y |
a character, the name of a numerical vector |
type |
a character which represents the type of
graph to display. If |
show |
a character which represents where the plot
should focus If |
numints |
a number of intervals for a density grid object. |
datasources |
a list of opal object(s) obtained
after login in to opal servers; these objects hold also
the data assign to R, as |
The function first generates a density grid and uses it to plot the graph. Cells of the grid density matrix that hold a count of less than the filter set by DataSHIELD (usually 5) are considered invalid and turned into 0 to avoid potential disclosure. A message is printed to inform the user about the number of invalid cells. The ranges returned by each study and used in the process of getting the grid density matrix are not the exact minumum and maximum values but rather close approximates of the real minimum and maximum value. This was done to reduce the risk of potential disclosure.
a heatmap plot
Isaeva, J.; Gaye, A.
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# load the file that contains the login details
data(logindata)
# login and assign the required variables to R
myvar <- list("LAB_TSC","LAB_HDL")
opals <- datashield.login(logins=logindata,assign=TRUE,variables=myvar)
# Example1: generate a combined (i.e. pooled heatmap plot)
ds.heatmapPlot(x='D$LAB_TSC', y='D$LAB_HDL')
ds.heatmapPlot(x='D$LAB_TSC', y='D$LAB_HDL', show='zoomed')
# Example2: generate a heatmapplot where each study is plotted seaparately
ds.heatmapPlot(x='D$LAB_TSC', y='D$LAB_HDL', type='split')
ds.heatmapPlot(x='D$LAB_TSC', y='D$LAB_HDL', type='split', show='zoomed')
# Example3: generate a heatmap plot with a less dense drid
ds.heatmapPlot(x='D$LAB_TSC', y='D$LAB_HDL', type='split', numints=15)
# clear the Datashield R sessions and logout
datashield.logout(opals)
}
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