R: Chemical portraits of cancer proteomes

R Documentation

Chemical portraits of cancer proteomes

Description

Plots from the papers by Dick (2016 and 2017).

Usage

  Ehplot(T = 37, pH = 7.4,
    xlim = c(-75, -55), ylim = c(-10, 10), dy = 0.2)
  rankdiff(rank1, rank2, n1 = NULL, n2 = NULL, as.fraction=TRUE)
  rankplot(pdat, T = 37, what = "rankdiff", main = NULL, res = 300,
    plot.it = TRUE, xlim = c(-75, -55), ylim = c(-10, 10), basis = "QEC+")
  groupplots(group = "hypoxia_ZC_down", each100 = FALSE, res = 50,
    plot.it = TRUE)
  mergedplot(gpresult, each100 = FALSE, res = 50)
  get_colors(x, max50 = FALSE)

Arguments

`T`	numeric, temperature in degrees Celsius
`pH`	numeric, pH
`xlim`	numeric, range of x axis
`ylim`	numeric, range of y axis
`basis`	character, basis species to use (see `basis`)
`dy`	numeric, y spacing between iso-logf_O₂ lines
`rank1`	numeric, ranks in group 1
`rank2`	numeric, ranks in group 2
`n1`	numeric, size of group 1
`n2`	numeric, size of group 2
`as.fraction`	logical, calculate the fraction of maximum possible difference?
`pdat`	list, data object generated by a `pdat_` function
`what`	character, “rankdiff” or “affinity”
`main`	character, text to use for title of plot
`res`	numeric, grid resolution for plot
`plot.it`	logical, draw a plot?
`group`	character, description of datasets to include
`each100`	logical, rescale rank difference of each dataset individually?
`gpresult`	list, value returned by `groupplots`
`x`	numeric values
`max50`	logical, use most intense color for all values >= 50?

Details

Ehplot

This function plots selected values of Eh (redox potential) as a function of logf_O₂ and loga_H₂O. The lines are labeled with the Eh value in volts. The temperature and pH can be adjusted using the T and pH arguments; this affects the lines, but not the positions of labels.

rankdiff

Calculate rank-sum difference between two groups, weighted by the sizes of the groups.

In a combined ranking of two groups, the comparison of sum of ranks has an easy interpretation only for groups of equal size. The weighted rank difference is used to compare groups of unequal size. The weighting ensures that 1) opposite extreme configurations give weighted rank differences with equal magnitudes, and 2) an evenly distributed (interspersed) ranking of the two groups has a weighted rank difference of zero (Dick, 2016).

If n1 and n2 are not given, rank1 and rank2 are interpreted as vectors holding the ranks for the two groups. If the sizes of the groups are supplied in n1 and n2, then the single values or higher-dimensional objects in rank1 and rank2 are interpreted as the non-weighted sums of ranks of the two groups.

rankplot

Plot ranking of chemical affinities of groups of proteins.

This function creates a loga_H₂O - logf_O₂ diagram showing the relative stabilities of the two groups of proteins in the specified dataset. These groups consist of the relatively down- and up-expressed proteins identified by up2 in one of the pdat_ functions.

The function generates a colored image and contour plot showing the weighted difference of sums of ranks of chemical affinities of formation of proteins in the two groups (see affinity and rankdiff). Increasing intensity of blue or red colors (see get_colors) represent higher rankings of the down-expressed (up2==FALSE) or up-expressed (up2==TRUE) proteins, respectively. Alternatively, if what is “affinity”, a maximum affinity diagram is produced (see diagram in CHNOSZ), with fields colored red or blue according to the relative expression of the protein.

If main is NULL, the title for the plot is taken from the description supplied in pdat.

Set plot.it to FALSE to skip the plotting and instead return a list containing the computed rank differences and x- and y- values and labels.

groupplots, mergedplot

Plot rank difference of chemical affinities for proteins in various datasets and merge the diagrams.

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 logf_O₂ and loga_H₂O 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 logf_O₂ and loga_H₂O.

get_colors

get_colors returns a diverging (blue - light gray - red) color scale. Blue and red colors are associated with negative and positive values, respectively. The intensity of the color increases with the magnitude of the value. For accurate representation, the values should be in a percent scale (i.e. the maximum absolute value is not greater than 100). By default, a value of +/- 100 corresponds to greatest intensity. Set max50 to TRUE to compress the scale so that greatest intesity is obtained at values of +/- 50 and higher.

These colors are used in rankplot. The colors were precomputed using colorspace::diverge_hcl.

Files in extdata/Dic16

microbes.csv, microbial.aa.csv: Data for microbial occurrence in colorectal cancer and normal tissue, and overall amino acid compositions of proteins in microbial species. The files are from the Supporting Information of Dick (2016).

Files in extdata/cpcp

colorectal.Rmd, hyperosmotic.Rmd, hypoxia.rmd, pancreatic.Rmd: Vignettes showing compositional analysis of differential protein expression, based on Figures 1-2 and Tables 1-4 of Dick (2017). Updated versions of these plots and the underlying datasets are in Dick (2020).
summary: Directory with CSV files summarizing compositional differences, used by groupplots.

References

Dick JM (2016) Proteomic indicators of oxidation and hydration state in colorectal cancer. PeerJ 4, e2238. doi:10.7717/peerj.2238

Dick JM (2017) Chemical composition and the potential for proteomic transformation in cancer, hypoxia, and hyperosmotic stress. PeerJ 5, e3421 doi:10.7717/peerj.3421

Dick JM (2021) Water as a reactant in the differential expression of proteins in cancer. Comp. Sys. Onco. 1:e1007. doi:10.1002/cso2.1007

Examples

Ehplot()

# rankings of H and C in H-H-H-H-C-C-C
rankdiff(1:4, 5:7, as.fraction=FALSE)  # 12
rankdiff(1:4, 5:7)  # 1
# rankings of H and C in C-C-C-H-H-H-H
rankdiff(4:7, 1:3, as.fraction=FALSE)  # -12
rankdiff(4:7, 1:3)  # -1
# rankings of H and C in H-C-H-C-H-C-H
rankdiff(c(1, 3, 5, 7), c(2, 4, 6))  # 0

pdat <- pdat_colorectal("JKMF10")
rankplot(pdat, res=25)
rankplot(pdat, res=25, what="affinity")

## Not run: 
gpresult <- groupplots("osmotic_H2O_down", res = 25)
mergedplot(gpresult, res = 25)

# make plots similar to 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)
}
## End(Not run)

[Package JMDplots version 1.2.19-14 Index]