Character string containing the name(s) of the color(s)
in which the profile(s) should be plotted.
standardize
If FALSE, the profile
values si are displayed as they are with the value
y=-b/L superimposed as a light gray line. If TRUE
(default), the profile(s) is/are shifted by the baseline values
-b/L and the light
gray line is displayed at y=0.
shades
Vector of at least two color specifications (default:
NULL). If not NULL, the background area above and below the base
line y=-b/L are shaded in colors shades[1] and
shades[2], respectively.
legend
A character string containing the legend/description of
the profile. If "default", the names of the
sequences/profiles are used. If no names are available, the profiles
are simply enumerated (as long as two profiles should be plot
together; if only a single unnamed profile is to be plotted, no
legend is shown). If legend is an empty string, no legend
is displayed at all.
legendPos
position specification for legend (if legend
is specified). Can either be a vector with
coordinates or a single keyword like
“topright” (see
legend).
xlab
label of horizontal axis, empty by default.
ylab
label of vertical axis, defaults to “weight”.
lwd.profile
profile line width as described for
parameter lwd in par
lwd.axis
axis line width as described for
parameter lwd in par
las
see par
heptads
if TRUE (default), the heptad structure
is indicated by vertical light gray lines separating the different
heptads. Heptad irregularities are indicated with red lines.
annotate
if TRUE (default), the heptad annotation
information is shown in the center of the plot.
...
all other arguments are passed to the
plot method from the
kebabs package
Details
The plot function displays a prediction profile as a step
function over the sequence with the steps connected by vertical lines.
The sequence and the heptad register are visualized below and above
the profile, respectively. The baseline value -b/L and the light
gray line has the following meaning: It is obvious that we can rewrite
f(x)=b+sum over all si(x) for i=1,… L
as
f(x)=sum over all (si(x) - (-b/L)) for i=1,… L,
so the discriminant function value f(x) can be understood
as the sum of values (si(x) - (-b/L)), i.e.
the area between the constant value -b/L and the prediction
profile. If the area above the light gray line is greater than
the area below the light gray line, the sequence is predicted as
trimer, otherwise as dimer.
If plot is called for a CCProfile object
that contains profiles of two sequences, the two profiles are plotted
together to facilitate a comparison of profiles (e.g. wild type
sequences versus mutants). Although the plot function tolerates
profiles/sequences with different lengths and/or unaligned heptad
registers, it is obvious that the superimposition of profiles of
two unaligned, unrelated sequences makes little sense.
The plot functions gives an error if is called for a
CCProfile object that contains profiles of
three or more sequences.
The given function is only a wrapper around the
plot function provided
by the kebabs package. The only difference is that heptad
seperators (argument heptads) and the heptad annotation
(argument annotate) are displayed by default.
Moreover, presently, no legend is displayed by default if a
single profile is plotted for an unnamed sequence.
Mahrenholz, C.C., Abfalter, I.G., Bodenhofer, U., Volkmer, R., and
Hochreiter, S. (2011) Complex networks govern coiled coil
oligomerization - predicting and profiling by means of a machine
learning approach. Mol. Cell. Proteomics 10(5):M110.004994.
DOI: 10.1074/mcp.M110.004994
Palme, J., Hochreiter, S., and Bodenhofer, U. (2015) KeBABS:
an R package for kernel-based analysis of biological sequences.
Bioinformatics 31(15):2574-2576. DOI: 10.1093/bioinformatics/btv176
See Also
procoil, CCModel,
CCProfile
Examples
## predict oligomerization of GCN4 wildtype
GCN4wt <- predict(PrOCoilModel,
"MKQLEDKVEELLSKNYHLENEVARLKKLV",
"abcdefgabcdefgabcdefgabcdefga")
## plot profile
plot(GCN4wt)
## define two GCN4 mutations
GCN4mSeq <- c("GCN4wt" ="MKQLEDKVEELLSKNYHLENEVARLKKLV",
"GCN4_N16I_L19N"="MKQLEDKVEELLSKIYHNENEVARLKKLV")
GCN4mReg <- rep("abcdefgabcdefgabcdefgabcdefga", 2)
## predict oligomerization
GCN4mut <- predict(PrOCoilModel, GCN4mSeq, GCN4mReg)
## overlay plot of the two profiles
plot(GCN4mut)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(procoil)
Loading required package: kebabs
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: XVector
Loading required package: kernlab
Attaching package: 'kernlab'
The following object is masked from 'package:Biostrings':
type
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/procoil/plot-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot-methods
> ### Title: Plotting prediction profiles
> ### Aliases: plot plot-methods plot,CCProfile,missing-method plot.CCProfile
> ### Keywords: classif models methods
>
> ### ** Examples
>
> ## predict oligomerization of GCN4 wildtype
> GCN4wt <- predict(PrOCoilModel,
+ "MKQLEDKVEELLSKNYHLENEVARLKKLV",
+ "abcdefgabcdefgabcdefgabcdefga")
>
> ## plot profile
> plot(GCN4wt)
>
> ## define two GCN4 mutations
> GCN4mSeq <- c("GCN4wt" ="MKQLEDKVEELLSKNYHLENEVARLKKLV",
+ "GCN4_N16I_L19N"="MKQLEDKVEELLSKIYHNENEVARLKKLV")
> GCN4mReg <- rep("abcdefgabcdefgabcdefgabcdefga", 2)
>
> ## predict oligomerization
> GCN4mut <- predict(PrOCoilModel, GCN4mSeq, GCN4mReg)
>
> ## overlay plot of the two profiles
> plot(GCN4mut)
>
>
>
>
>
> dev.off()
null device
1
>