get_comptab: Calculate Differences of Chemical Metrics
In canprot: Chemical Metrics of Differentially Expressed Proteins

Description Usage Arguments Details Value References Examples

Compute differences of carbon oxidation state, stoichiometric hydration state and other chemical metrics between groups of up- and down-regulated proteins.

1 2	get_comptab(pdat, var1 = "ZC", var2 = "nH2O", plot.it = FALSE, mfun = "median", oldstyle = FALSE, basis = getOption("basis"))

`pdat`	list, data object generated by a `pdat_` function
`var1`	character, the first variable
`var2`	character, the second variable
`plot.it`	logical, make a scatterplot?
`mfun`	character, either median or mean
`oldstyle`	logical, also calculate `CLES` and p-values?
`basis`	character, keyword for basis species to use

The available variables are:

ZC	average oxidation state of carbon (\ZC; see `ZCAA`)
nH2O	stoichiometric hydration state per residue (\nH2O; see `H2OAA`)
nO2	stoichiometric oxidation state per residue (\nO2; see `O2AA`)
V0	standard molal volume per residue
nAA	protein length (number of amino acids)
GRAVY	grand average of hydropathicity (see `GRAVY`)
pI	isoelectric point (see `pI`)
MW	molecular weight per residue

Differentially expressed proteins are identified by the value of pdat$up2 (TRUE for up-regulated proteins and FALSE for down-regulated proteins). The differences are calculated as (median for up-regulated proteins) - (median for down-regulated proteins); if mfun is mean, means of the groups are used instead. If oldstyle is TRUE, the function also calculates the common language effect size (CLES, in percent) and p-value for each variable.

The basis argument is used to select the basis species, which are used for the calculation of \nH2O and \nO2. The default for getOption("basis") is to use the QEC basis species (see metrics).

Volume is calculated using amino acid group additivity as described by Dick et al. (2006).

Set plot.it to TRUE to make a scatterplot. Open red squares and filled blue circles stand for up-regulated and down-regulated proteins, respectively.

A data frame is returned invisibly containing the columns dataset, description, n1 (number of down-regulated proteins), n2 (number of up-regulated proteins), followed two sets of columns for the variables. These are denoted generically as (var.mfun1, var.mfun2, var.diff, var.CLES, var.p.value), where var is replaced by the name of var1 or var2, and mfun is replaced by the value of mfun. For example, ZC.median1 and ZC.median2 are the median \ZC of the down- and up-regulated proteins, respectively.

Dick, J. M., LaRowe, D. E. and Helgeson, H. C. (2006) Temperature, pressure, and electrochemical constraints on protein speciation: Group additivity calculation of the standard molal thermodynamic properties of ionized unfolded proteins. Biogeosciences 3, 311–336. doi: 10.5194/bg-3-311-2006

pd <- pdat_colorectal("JKMF10")
# default variables: ZC and nH2O
get_comptab(pd, plot.it = TRUE)
# protein length and per-residue volume
get_comptab(pd, "nAA", "V0", plot.it = TRUE)