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hyginn 2019-11-14 22:44:07 -05:00
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RPR-SX-PDB.R
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@ -3,12 +3,13 @@
# Purpose: A Bioinformatics Course:
# R code accompanying the RPR-SX-PDB unit.
#
# Version: 1.1
# Version: 1.2
#
# Date: 2017 10 - 2019 01
# Date: 2017 10 - 2019 11
# Author: Boris Steipe (boris.steipe@utoronto.ca)
#
# Versions:
# 1.2 Maintenance
# 1.1 Change from require() to requireNamespace(),
# use <package>::<function>() idiom throughout
# 1.0 First live version, completely refactores 2016 code
@ -33,18 +34,18 @@
#TOC>
#TOC> Section Title Line
#TOC> ----------------------------------------------------------
#TOC> 1 Introduction to the bio3D package 61
#TOC> 2 A Ramachandran plot 152
#TOC> 3 Density plots 228
#TOC> 3.1 Density-based colours 242
#TOC> 3.2 Plotting with smoothScatter() 261
#TOC> 3.3 Plotting hexbins 276
#TOC> 3.4 Plotting density contours 304
#TOC> 3.4.1 ... as overlay on a colored grid 337
#TOC> 3.4.2 ... as filled countour 354
#TOC> 3.4.3 ... as a perspective plot 385
#TOC> 4 cis-peptide bonds 403
#TOC> 5 H-bond lengths 418
#TOC> 1 Introduction to the bio3D package 62
#TOC> 2 A Ramachandran plot 153
#TOC> 3 Density plots 229
#TOC> 3.1 Density-based colours 243
#TOC> 3.2 Plotting with smoothScatter() 262
#TOC> 3.3 Plotting hexbins 277
#TOC> 3.4 Plotting density contours 305
#TOC> 3.4.1 ... as overlay on a coloured grid 338
#TOC> 3.4.2 ... as filled countour 355
#TOC> 3.4.3 ... as a perspective plot 386
#TOC> 4 cis-peptide bonds 404
#TOC> 5 H-bond lengths 419
#TOC>
#TOC> ==========================================================================
@ -166,7 +167,7 @@ abline(v = 0, lwd = 0.5, col = "#00000044")
# quadrant of the plot. This combination of phi-psi angles defines
# the conformation of a left-handed alpha helix and is generally
# only observed for glycine residues. Let's replot the data, but
# color the points for glycine residues differently. First, we
# colour the points for glycine residues differently. First, we
# get a vector of glycine residue indices in the structure:
mySeq <- bio3d::pdbseq(apses)
@ -242,7 +243,7 @@ for (i in 1:nrow(dat)) {
# == 3.1 Density-based colours =============================================
# A first approximation to scatterplots that visualize the density of the
# underlying distribution is coloring via the densCols() function.
# underlying distribution is colouring via the densCols() function.
?densCols
iNA <- c(which(is.na(tor$phi)), which(is.na(tor$psi)))
phi <- tor$phi[-iNA]
@ -334,7 +335,7 @@ str(dPhiPsi)
contour(dPhiPsi)
# === 3.4.1 ... as overlay on a colored grid
# === 3.4.1 ... as overlay on a coloured grid
image(dPhiPsi,
col = myColorRamp(100),
@ -633,7 +634,7 @@ hist(dH)
hist(dE)
# add color:
# add colour:
hist(dH, col="#DD0055")
hist(dE, col="#00AA70")
@ -653,7 +654,7 @@ hist(dH, col="#DD0055")
hist(dE, col="#00AA70", add=TRUE)
# We see that the leftmost column of the sheet bonds hides the helix bonds in
# that column. Not good. But we can make the colors transparent! We just need to
# that column. Not good. But we can make the colours transparent! We just need to
# add a fourth set of two hexadecimal-numbers to the #RRGGBB triplet. Lets use
# 2/3 transparent, in hexadecimal, 1/3 of 256 is x55 - i.e. an RGB triplet
# specied as #RRGGBB55 is only 33% opaque:
@ -712,7 +713,7 @@ legend("topright",
# it is easy to try this with a larger protein.
# 3ugj for example is VERY large.
pdb <- read.pdb("3ugj")
pdb <- bio3d::read.pdb("3ugj")
# helices...
iN <- ssSelect(pdb, ssType = c("helix"), myElety = "N")
@ -769,7 +770,7 @@ dH <- c() # collect all helix H-bonds here
dE <- c() # collect all sheet H-bonds here
for (i in seq_along(myPDBs)) {
pdb <- read.pdb(myPDBs[i])
pdb <- bio3d::read.pdb(myPDBs[i])
# helices...
iN <- ssSelect(pdb, ssType = c("helix"), myElety = "N")
@ -786,7 +787,7 @@ for (i in seq_along(myPDBs)) {
# Inspect the results
length(dH) # 4415 (your numbers are different, but it should be a lot)
length(dH) # 4415 (your numbers are different, but there should be many)
length(dE) # 262
brk=seq(2.0, 4.0, 0.1)