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Plot rank difference of chemical affinities for proteins in various datasets and merge the diagrams.
groupplots(group = "hypoxia_ZC_down", each100 = FALSE, res = 50, plot.it = TRUE)
mergedplot(gpresult, each100 = FALSE, res = 50)
character, description of datasets to include
logical, rescale rank difference of each dataset individually?
numeric, grid resolution for plots
logical, make plots?
list, value returned by groupplots
groupplots
makes weighted rank-difference of affinity (potential) diagrams (see rankplot
) for each dataset found in the specified group
.
group
consists of three parts joined by an underscore: the type of experiment (colorectal, pancreatic, hypoxia, or osmotic; see pdat_
), the distinguishing compositional variable (ZC or H2O), and the direction of change of that variable (up or down).
To identify the datasets in any group, compositional summaries for each dataset are read from pre-calculated tables in extdata/summary
.
Datasets are included for which the absolute mean difference of either ZC or H2O between up- and down-expressed proteins is greater than 0.01 and the other of ZC or H2O has p-value >= 0.05 and abs(CLES
- 50) < 10.
groupplots
makes calculations over a large range of and in order to encompass the equipotential lines for most datasets.
This way, the positions of the median and interquartiles of the equipotential lines can be calculated accurately for the mergedplot
, which covers a smaller range of and .
This function is used in the historical vignette inst/oldvignettes/potential_diagrams.Rmd
.
rankplot
and rankdiff
are supporting functions.
# NOT RUN {
gpresult <- groupplots("osmotic_H2O_down", res = 25)
mergedplot(gpresult, res = 25)
# reproduce Figure 3 of Dick, 2017
ZCgroups <- c("colorectal_ZC_up", "pancreatic_ZC_up", "hypoxia_ZC_down")
H2Ogroups <- c("colorectal_H2O_up", "pancreatic_H2O_up", "osmotic_H2O_down")
allgroups <- c(ZCgroups, H2Ogroups)
par(mfrow=c(2, 3))
for(group in allgroups) {
gpresult <- groupplots(group, plot.it = FALSE)
mergedplot(gpresult)
title(main = group)
}
# }
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