Description Usage Arguments Value See Also Examples
Plots a diagram of protein structure based on several types of annotations and predictions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | plot_prot(
sequence,
id,
hyp_col = "#868686FF",
gpi_col = "#0073C2FF",
nsp_col = "#CD534CFF",
ag_col = "#E5E5E5FF",
tm_col = "#EFC000FF",
hyp = TRUE,
gpi = c("bigpi", "predgpi", "netgpi", "none"),
nsp = c("signalp", "signalp5", "none"),
ag = TRUE,
tm = c("phobius", "tmhmm", "none"),
domain = c("cdd", "hmm", "none"),
disorder = FALSE,
hyp_scan = if (ag == TRUE && hyp == TRUE) TRUE else FALSE,
dom_sort = c("ievalue", "abc", "cba"),
progress = FALSE,
gpi_size = 4,
gpi_shape = 18,
...
)
|
sequence |
String representing a protein amino acid sequence. |
id |
String representing a protein identifier. Will be converted using |
hyp_col |
Plotting color of predicted hydroxyproline positions. At default set to: '#868686FF'. |
gpi_col |
Plotting color of the predicted omega site (glycosylphosphatidylinositol attachment). At default set to: '#0073C2FF'. |
nsp_col |
Plotting color of the N-terminal signal peptide. At default set to: '#CD534CFF'. |
ag_col |
Plotting color of the AG glycomodul spans. At default set to: '#E5E5E5FF'. |
tm_col |
Plotting color of the transmembrane regions. At default set to: '#EFC000FF'. |
hyp |
Boolean, should hydroxyprolines be plotted. |
gpi |
A string indicating if |
nsp |
A string indicating if |
ag |
Boolean, should the AG glycomodul spans be plotted. |
tm |
A string indicating if |
domain |
A string indicating if |
disorder |
Boolean, should disordered region predictions obtained using |
hyp_scan |
Boolean, if ag = TRUE, should |
dom_sort |
One of c("ievalue", "abc", "cba"), defaults to "ievalue". Domain plotting order. If 'ievalue' domains with the lowest ievalue as determined by hmmscan will be plotted above. If 'abc' or 'cba' the order is determined by domain Names. |
progress |
Boolean, whether to show the progress bar, at default set to FALSE. |
gpi_size |
Integer, the size of the gpi symbol. Appropriate values are 1 - 10. |
gpi_shape |
Integer, the shape of the gpi symbol. Appropriate values are 0 - 25 |
... |
Appropriate arguments passed to |
A ggplot2 plot object
get_signalp5
get_signalp
get_phobius
get_tmhmm
get_hmm
get_cdd
get_espritz
predict_hyp
scan_ag
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | library(ragp)
library(ggplot2)
ind <- c(23, 5, 80, 81, 345)
pred <- plot_prot(sequence = at_nsp$sequence[ind],
id = at_nsp$Transcript.id[ind])
pred +
theme(legend.position = "bottom",
legend.direction = "vertical")
#alternatively:
nsp <- get_signalp(data = at_nsp[ind,],
id = Transcript.id,
sequence = sequence)
hmm <- get_hmm(data = at_nsp[ind,], #default is to use get_cdd()
id = Transcript.id,
sequence = sequence)
gpi <- get_netGPI(data = at_nsp[ind,],
id = Transcript.id,
sequence = sequence)
tm <- get_phobius(data = at_nsp[ind,],
id = Transcript.id,
sequence = sequence)
disorder <- get_espritz(data = at_nsp[ind,],
id = Transcript.id,
sequence = sequence)
pred2 <- plot_prot(sequence = at_nsp$sequence[ind],
id = at_nsp$Transcript.id[ind],
tm = tm,
nsp = nsp,
gpi = gpi,
domain = hmm,
disorder = disorder)
pred2 +
theme(legend.position = "bottom",
legend.direction = "vertical")
#mixing both methods is also a possibility
|
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