Deleted old folders

FigurePaper/example2/transcriptionfactors.R

-#!/usr/bin/Rscript
-## EXAMPLE 2
-## Description: From a dataset of DNA-TF, plot the most frequent amino acids
-##              interacting with phosphate, sugar and base.
-## Author: Diego Gallego
-
-## ----------------------------------------------------------------------------
-## Preprocess
-## ----------------------------------------------------------------------------
-## Load necessary packages for the example
-library(veriNA3d)
-library(bio3d)
-
-plotAA <- function(ta, main) {
-    color <- rainbow(n=20)
-    names(color) <- c("ALA", "ARG", "ASN", "ASP", "CYS", "GLN", "GLU", "GLY", 
-                        "HIS", "ILE", "LEU", "LYS", "MET", "PHE", "PRO", "SER",
-                        "THR", "TRP", "TYR", "VAL")
-    par(mar=c(0, 3, 1, 0.6))
-    a <- barplot(ta[5:1]/sum(ta), xlim=c(0, 0.7), las=2, border=0,
-                    #cex.lab=1, cex.axis=1, font=1, col=color[names(ta[1:5])],
-                    xaxt='n', font=1, col=color[names(ta[5:1])],
-                    cex.names=1.5, main=main, cex.main=1.5, horiz=TRUE)
-}
-
-## ----------------------------------------------------------------------------
-## Get Raw data
-cat("Getting data\n")
-## ----------------------------------------------------------------------------
-
-path <- "transcription_factor_pdb/"
-pdblist <- dir(path, pattern=".ent.gz")
-pdblist <- gsub(".ent.gz", "", pdblist)
-
-## Get structural data
-aantinfo <- pipeProtNucData(pdbID=pdblist, path=path, 
-                            extension=".ent.gz", cutoff=10, cores=1)
-
-## ----------------------------------------------------------------------------
-## Clean data. Raw -> Tidy
-cat("Cleaning data\n")
-## ----------------------------------------------------------------------------
-
-## Filter to keep only closest contacts using distance < 3 Angstroms
-intdata <- aantinfo[aantinfo$distance < 3, ]
-
-## Create objects of interest
-P <- c("OP1", "OP2", "OP3")
-S <- c("O4'", "O3'", "O5'")
-B <- c("N1", "N2", "N3", "N4", "N6", "N7", "O2", "O4", "O6")
-
-ta_P <- sort(table(intdata[intdata$elety_A %in% P, "resid_B"]), decreasing=TRUE)
-ta_S <- sort(table(intdata[intdata$elety_A %in% S, "resid_B"]), decreasing=TRUE)
-ta_B <- sort(table(intdata[intdata$elety_A %in% B, "resid_B"]), decreasing=TRUE)
-
-## ----------------------------------------------------------------------------
-## Exploratory analysis. Plot
-cat("Plotting data\n")
-## ----------------------------------------------------------------------------
-
-total <- sum(ta_P, ta_S, ta_B)
-tiff("example2.tiff", height=10.5, width=16.5, units="cm", res=300)
-par(mfrow=c(3, 1), oma=c(4.5, 1, 1, 1))
-## Phosphate interactions plot
-plotAA(ta_P, main=paste("Phosphate ", round(sum(ta_P)/total*100), "%", sep=""))
-## Sugar interactions plot
-plotAA(ta_S, main=paste("Sugar ", round(sum(ta_S)/total*100), "%", sep=""))
-## Base interactions plot
-plotAA(ta_B, main=paste("Base ", round(sum(ta_B)/total*100), "%", sep=""))
-axis(side=1, lwd=1.5, cex.axis=2)
-title(xlab="Density", cex.lab=2, outer=TRUE)
-dev.off()

FigurePaper/example3/rnamg.R

-#!/usr/bin/Rscript
-## EXAMPLE 3
-## Description: From the whole PDB, create a dataset of RNA structures with Mg
-##              and a threshold resolution of 2 Angstroms. Then, measure and
-##              plot the distances between Mg and other atom types.
-## Author: Diego Gallego
-
-## ----------------------------------------------------------------------------
-## Preprocess
-## ----------------------------------------------------------------------------
-## Load necessary packages for the example
-library(veriNA3d)
-library(ggplot2) ## Specific dependency for this example!
-library(reshape2) ## Specific dependency for this example!
-
-## ----------------------------------------------------------------------------
-## Get Raw data
-cat("Getting data\n")
-## ----------------------------------------------------------------------------
-## From the whole PDB, prepare dataset of interest ============================
-## Retrieve ALL entries in the PDB (including latest entries)
-pdblist <- queryEntryList(justIDs=FALSE)
-
-## Keep only Nucleic Acid structures solved by diffraction techniques
-nalist <- pdblist[which(grepl("nuc", pdblist$type, perl=TRUE) & 
-                        pdblist$technique == "diffraction"), "pdbID"]
-
-## Query which structures contain MG
-mg <- toupper(unlist(queryAPI(ID="MG", API="ebi", verbose=TRUE,
-                                string1="pdb/compound/in_pdb/", string2="")))
-mgnalist <- nalist[which(nalist %in% mg)]
-
-## Query resolution and keep only structures under 2 A
-resol <- applyToPDB(mgnalist, queryResol)
-mgnalist <- resol[resol[, 2] < 2, 1]
-
-## Check entities in the structures and keep only PDBs with RNA
-naent <- applyToPDB(mgnalist, countEntities, as.df=FALSE)
-naent <- as.data.frame(do.call(rbind, naent), stringsAsFactors=FALSE)
-mgrnalist <- mgnalist[which(naent$RNA > 0)]
-## ============================================================================
-
-## Loop over list of PDB IDs
-distances <- do.call(rbind, lapply(seq_along(mgrnalist), function(i) {
-    ## Download mmCIF and get entity of Mg
-    cif <- cifParser(mgrnalist[i])
-    MG <- cifEntity(cif)[grepl("MAGNE", cifEntity(cif)$pdbx_description), "id"]
-
-    ## Measure distances between Mg and other entities
-    return(measureEntityDist(cif, refent=MG, entities="all", cutoff=4, n=NULL))
-}))
-
-## ----------------------------------------------------------------------------
-## Clean data. Raw -> Tidy
-cat("Cleaning data\n")
-## ----------------------------------------------------------------------------
-Ow <- distances$distance[distances$resid_B == "HOH" & distances$elety_B == "O"]
-distances <- distances[distances$resid_B %in% c("A", "C", "G", "U"), ]
-Ob <- distances$distance[distances$elety_B %in% c("O2", "O4", "O6")]
-Or <- distances$distance[distances$elety_B %in% c("O2'", "O3'", "O4'", "O5'")]
-Op <- distances$distance[distances$elety_B %in% c("OP1", "OP2", "OP3")]
-Nb <- distances$distance[distances$elety_B %in% c("N1", "N2", "N3", "N7")]
-## Data frame with distances per type of aotm
-dist <- list(Nb=Nb, Ob=Ob, Or=Or, Op=Op, Ow=Ow)
-df <- melt(dist, value.name="Distance"); names(df)[2] <- "atom"
-df$atom <- factor(df$atom, levels=c("Ow", "Op", "Or", "Ob", "Nb"))
-
-## ----------------------------------------------------------------------------
-## Exploratory analysis. Plot
-cat("Plotting data\n")
-## ----------------------------------------------------------------------------
-tiff("example3.tiff", height=10.5, width=16.5, units="cm", res=300)
-colors <- c("#87CEEB", "#6A5ACD", "#F08080", "#DC143C", "#4169E1")
-ggplot(df, aes(x=Distance, fill=atom)) + ylab("Frequency") + 
-        scale_fill_manual(values=colors) + scale_y_continuous(breaks=NULL) +
-        scale_x_continuous(breaks=seq(1.2, 4, 0.4)) +
-        geom_histogram(binwidth=0.03, color="white") +
-        theme(panel.grid.minor=element_blank())
-dev.off()

FigurePaper/example4/dependencies.R

-## plotM plots a pie chart using ggplot
-plotM <- function(x, res, motifs=motifs, motifs2=motifs2) {
-    df <- data.frame(table(x))
-    names(df) <- c("motif", "value")
-    df <- df[order(df$value), ]
-    fa <- factor(levels(df$motif), levels=c(motifs, motifs2))
-
-    pie <- ggplot(df, aes(x="", y=value, fill=motif)) +
-                    geom_bar(width = 1, stat = "identity") +
-                    coord_polar("y", start=0)
-
-    blank_theme <- theme_minimal()+
-                    theme(axis.title.x = element_blank(),
-                    axis.title.y = element_blank(),
-                    panel.border = element_blank(),
-                    panel.grid=element_blank(),
-                    axis.ticks = element_blank(),
-                    plot.title=element_text(size=14, face="bold"))
-
-    pie + scale_fill_manual(values=rainbow(length(levels(fa)))[fa]) + blank_theme +
-        theme(axis.text.x=element_blank()) + labs(title=res)
-}

FigurePaper/example4/modbase.R

-#!/usr/bin/Rscript
-## EXAMPLE 4
-## Description: Get lists of PDBs containing a 3 RNA modified residues,
-##              then filter by resolution and execute DSSR. Plot motif in which
-##              the modified residues are found.  
-## Author: Diego Gallego
-
-## ----------------------------------------------------------------------------
-## Preprocess
-## ----------------------------------------------------------------------------
-## Load necessary packages for the example
-library(veriNA3d)
-library(ggplot2) ## Specific dependency for this example!
-library(gridExtra) ## Specific dependency for this example!
-library(scales) ## Specific dependency for this example!
-
-## Load specific functions for the example
-source("dependencies.R")
-
-## ----------------------------------------------------------------------------
-## Get Raw data
-cat("Getting and cleaning data\n")
-## ----------------------------------------------------------------------------
-modres <- c("1MA", "6MA", "4SU")
-motifs <- c("hairpin-loop", "junction-loop", "ss-non-loop", "internal-loop")
-motifs2 <- c("helix")#, "helix-end")
-
-out <- lapply(modres, function(res) {
-    ## Query which structures contain the modres of interest
-    pdblist <- toupper(unlist(queryAPI(ID=res, API="ebi", verbose=TRUE,
-                                string1="pdb/compound/in_pdb/", string2="")))
-
-    ## Query resolution and keep only structures under 3 A
-    resol <- applyToPDB(pdblist, queryResol)
-    pdblist <- resol[resol[, 2] < 3, 1]
-
-    output <- c(); counter <- 0
-    ## Loop over list of PDB IDs
-    for (i in seq_along(pdblist)) {
-        tryCatch({
-                ## Execute DSSR
-                dssrdata <- dssr(pdblist[i])
-## ----------------------------------------------------------------------------
-## Clean data. Raw -> Tidy
-## ----------------------------------------------------------------------------
-                ## Extract data of interest
-                data <- dssrdata$models$parameters$nts[[1]]
-                summary <- data$summary[data$nt_name == res]
-                for (j in seq_along(summary)) {
-                    dat <- unlist(strsplit(summary[j], ","))
-                    ind <- which(dat %in% motifs)
-                    if (length(ind) == 0) {
-                        ind <- which(dat %in% motifs2)
-                    }
-                    if (length(ind) != 0) {
-                        counter <- counter + 1
-                        output[counter] <- dat[ind]
-                        in2 <- which(data$nt_name == res)
-                        ## Save neigbouring sequence
-                        write(c(dat[ind], 
-                                paste(data$nt_name[(in2-2):(in2+2)], collapse="-")), 
-                                file="seq.txt", ncolumns=2, append=T, sep=" ")
-                    }
-                }
-            ## If DSSR fails with the given structure, do nothing
-            }, error=function(e) {})
-    }
-    return(output)
-})
-## ----------------------------------------------------------------------------
-## Exploratory analysis. Plot
-cat("Plotting data\n")
-## ----------------------------------------------------------------------------
-p <- lapply(1:3, function(i) {
-    plotM(out[[i]], res=modres[i], motifs=motifs, motifs2=motifs2)
-})
-tiff("example4.tiff", height=10.5, width=24.75, units="cm", res=300)
-grid.arrange(p[[1]], p[[2]], p[[3]], ncol=3)
-dev.off()

FigurePaper/example4/seq.txt

-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-A-1MA-G-U
-hairpin-loop C-A-1MA-G-U
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-A-U
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop U-G-1MA-A-A
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop C-G-1MA-U-C
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop C-G-1MA-C-U
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop C-G-1MA-U-C
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop U-G-1MA-A-A
-hairpin-loop C-G-1MA-U-C
-hairpin-loop U-G-1MA-A-A
-hairpin-loop C-A-1MA-G-U
-internal-loop U-C-1MA-C-G
-ss-non-loop U-C-1MA-C-G
-ss-non-loop U-C-1MA-C-G
-internal-loop U-C-1MA-C-G
-internal-loop U-C-1MA-C-G
-hairpin-loop U-G-1MA-A-A
-internal-loop U-G-1MA-A-A
-hairpin-loop C-G-1MA-U-C
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-internal-loop DG-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-internal-loop DA-DG-6MA-DT-DC
-helix DA-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DA-DG-6MA-DT-DC
-helix DA-DG-6MA-DT-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DA-DC
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-helix DC-DG-6MA-DT-DC
-helix DA-DT-6MA-DG-DC
-helix DG-DA-6MA-DT-DT
-helix DG-DA-6MA-DT-DT
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-helix DG-DG-6MA-DT-DC
-internal-loop DA-DA-6MA-DA-DC
-internal-loop DA-DA-6MA-DA-DC
-internal-loop DA-DA-6MA-DA-DC
-internal-loop DA-DA-6MA-DA-DC
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-helix DT-DG-6MA-DT-DT
-junction-loop G-U-4SU-A-A
-junction-loop G-G-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-ss-non-loop U-A-4SU-C-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop C-G-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-U-A
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-hairpin-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-ss-non-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-U-4SU-G-A
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-G-4SU-G-G
-junction-loop G-G-4SU-G-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop G-A-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G
-junction-loop A-U-4SU-A-G