### R code from vignette source 'GraphPAC.Rnw' ################################################### ### code chunk number 1: Example1 ################################################### library(GraphPAC) #Extract the data from a CIF file and match it up with the canonical protein sequence. #Here we use the 3GFT structure from the PDB, which corresponds to the KRAS protein. CIF<-"http://www.pdb.org/pdb/files/3GFT.cif" Fasta<-"http://www.uniprot.org/uniprot/P01116-2.fasta" KRAS.Positions<-get.Positions(CIF,Fasta, "A") #Load the mutational data for KRAS. Here the mutational data was obtained from the #COSMIC database (version 58). data(KRAS.Mutations) #Identify and report the clusters. my.graph.clusters <- GraphClust(KRAS.Mutations,KRAS.Positions$Positions, insertion.type = "cheapest_insertion", alpha = 0.05, MultComp = "Bonferroni") my.graph.clusters ################################################### ### code chunk number 2: Example2a ################################################### #Using the heat color palette Plot.Protein.Linear(my.graph.clusters$candidate.path, 25, color.palette = "heat", title = "Protein Reordering - Heat Map") ################################################### ### code chunk number 3: Example2b ################################################### #Using the gray color palette Plot.Protein.Linear(my.graph.clusters$candidate.path, 25, color.palette = "gray", title = "Protein Reordering - Gray Color Scale") ################################################### ### code chunk number 4: Example3 (eval = FALSE) ################################################### ## ## #Using the heat color palette ## Plot.Protein(my.graph.clusters$protein.graph, my.graph.clusters$candidate.path, ## vertex.size=5, color.palette="heat") ################################################### ### code chunk number 5: Example4 ################################################### library(RMallow) graph.path <-my.graph.clusters$candidate.path #get.Remapped.Order is a function in the \iPAC package mds.path <- get.Remapped.Order(KRAS.Mutations,KRAS.Positions$Positions) path.matrix <- rbind (original.seq = sort(graph.path), graph.path, mds.path) AllSeqDists(path.matrix)