## ----------------------------------------------------------------------------- library(geneplast) data(gpdata.gs) ## ----label='newOgp', eval=TRUE------------------------------------------------ ogp <- gplast.preprocess(cogdata=cogdata, sspids=sspids, cogids=cogids, verbose=FALSE) ## ----label='gplastTest', eval=TRUE-------------------------------------------- ogp <- gplast(ogp, verbose=FALSE) ## ----label='gplastRes', eval=TRUE--------------------------------------------- res <- gplast.get(ogp, what="results") head(res) ## ----label='newOgr', eval=TRUE------------------------------------------------ ogr <- groot.preprocess(cogdata=cogdata, phyloTree=phyloTree, spid="9606", verbose=FALSE) ## ----label='grootTest', eval=TRUE--------------------------------------------- set.seed(1) ogr <- groot(ogr, nPermutations=100, verbose=FALSE) # Note: nPermutations is set to 100 for demonstration purposes; please set nPermutations=1000 ## ----label='grootRes1', eval=TRUE--------------------------------------------- res <- groot.get(ogr, what="results") head(res) ## ----label='grootRes2', eval=TRUE--------------------------------------------- groot.plot(ogr, whichOG="NOG40170") ## ----label='rootRes', eval=TRUE----------------------------------------------- groot.plot(ogr, plot.lcas = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # # source("https://bioconductor.org/biocLite.R") # # biocLite("geneplast.data.string.v91") # library(geneplast.data.string.v91) # data(gpdata_string_v91) ## ----eval=FALSE--------------------------------------------------------------- # ogr <- groot.preprocess(cogdata=cogdata, phyloTree=phyloTree, spid="9606") ## ----eval=FALSE--------------------------------------------------------------- # ogr <- groot(ogr, nPermutations=100, verbose=TRUE) ## ----eval=FALSE--------------------------------------------------------------- # library(RedeR) # library(igraph) # library(RColorBrewer) # data(ppi.gs) ## ----eval=FALSE--------------------------------------------------------------- # g <- ogr2igraph(ogr, cogdata, ppi.gs, idkey = "ENTREZ") ## ----eval=FALSE--------------------------------------------------------------- # pal <- brewer.pal(9, "RdYlBu") # color_col <- colorRampPalette(pal)(25) # g <- att.setv(g=g, from="Root", to="nodeColor", # cols=color_col, na.col="grey80", # breaks=seq(1,25)) ## ----eval=FALSE--------------------------------------------------------------- # g <- att.setv(g = g, from = "SYMBOL", to = "nodeAlias") # E(g)$edgeColor <- "grey80" # V(g)$nodeLineColor <- "grey80" ## ----eval=FALSE--------------------------------------------------------------- # rdp <- RedPort() # calld(rdp) # resetd(rdp) # addGraph(rdp, g) # addLegend.color(rdp, colvec=g$legNodeColor$scale, # size=15, labvec=g$legNodeColor$legend, # title="Roots represented in Fig4") # relax(rdp) ## ----eval=FALSE--------------------------------------------------------------- # myTheme <- list(nestFontSize=25, zoom=80, isNest=TRUE, gscale=65, theme=2) # nestNodes(rdp, nodes=V(g)$name[V(g)$Apoptosis==1], # theme=c(myTheme, nestAlias="Apoptosis")) # nestNodes(rdp, nodes=V(g)$name[V(g)$GenomeStability==1], # theme=c(myTheme, nestAlias="Genome Stability")) # relax(rdp, p1=50, p2=50, p3=50, p4=50, p5= 50) ## ----eval=FALSE--------------------------------------------------------------- # library(RTN) # library(Fletcher2013b) # library(RedeR) # library(igraph) # library(RColorBrewer) # data("rtni1st") ## ----eval=FALSE--------------------------------------------------------------- # regs <- c("FOXM1","PTTG1") # g <- tni.graph(rtni1st, gtype = "rmap", regulatoryElements = regs) ## ----eval=FALSE--------------------------------------------------------------- # g <- ogr2igraph(ogr, cogdata, g, idkey = "ENTREZ") ## ----eval=FALSE--------------------------------------------------------------- # pal <- brewer.pal(9, "RdYlBu") # color_col <- colorRampPalette(pal)(25) # g <- att.setv(g=g, from="Root", to="nodeColor", # cols=color_col, na.col = "grey80", # breaks = seq(1,25)) ## ----eval=FALSE--------------------------------------------------------------- # idx <- V(g)$SYMBOL %in% regs # V(g)$nodeFontSize[idx] <- 30 # V(g)$nodeFontSize[!idx] <- 1 # E(g)$edgeColor <- "grey80" # V(g)$nodeLineColor <- "grey80" ## ----eval=FALSE--------------------------------------------------------------- # rdp <- RedPort() # calld(rdp) # resetd(rdp) # addGraph(rdp, g, layout=NULL) # addLegend.color(rdp, colvec=g$legNodeColor$scale, # size=15, labvec=g$legNodeColor$legend, # title="Roots represented in Fig4") # relax(rdp, 15, 100, 20, 50, 10, 100, 10, 2) ## ----label='runtime', eval=FALSE---------------------------------------------- # #--- Load ggplot # library(ggplot2) # library(ggthemes) # library(egg) # library(data.table) # # #--- Load cogdata # data(gpdata.gs) # # #--- Get "OGs" that include a ref. species (e.g. "9606") # cogids <- unique(cogdata$cog_id[cogdata$ssp_id=="9606"]) # length(cogids) # # [1] 142 # # #--- Make a function to check runtime for different input sizes # check.rooting.runtime <- function(n){ # cogids.subset <- cogids[1:n] # cogdata.subset <- cogdata[cogdata$cog_id%in%cogids.subset,] # rt1 <- system.time( # ogr <- groot.preprocess(cogdata=cogdata.subset, phyloTree=phyloTree, # spid="9606", verbose=FALSE) # )["elapsed"] # rt2 <- system.time( # ogr <- groot(ogr, nPermutations=100, verbose=FALSE) # )["elapsed"] # rtime <- c(rt1,rt2) # names(rtime) <- c("runtime.preprocess","runtime.groot") # return(rtime) # } # # check.rooting.runtime(n=5) # # #--- Run check.rooting.runtime() for different input sizes (x3 iterations) # input_size <- seq.int(10,length(cogids),10) # iterations <- 1:3 # elapsed_lt <- lapply(iterations, function(i){ # print(paste0("Iteration ",i)) # it <- sapply(input_size, function(n){ # print(paste0("- size...",n)) # check.rooting.runtime(n) # }) # }) # # #--- Get 'preprocess' runtime # runtime.preprocess <- sapply(elapsed_lt, function(lt){ # lt["runtime.preprocess",] # }) # runtime.preprocess <- data.frame(InputSize=input_size, runtime.preprocess) # runtime.preprocess <- melt(as.data.table(runtime.preprocess), "InputSize") # colnames(runtime.preprocess) <- c("Input.Size","Iteration","Elapsed.Time") # # #--- Get 'groot' runtime # runtime.groot <- sapply(elapsed_lt, function(lt){ # lt["runtime.groot",] # }) # runtime.groot <- data.frame(InputSize=input_size, runtime.groot) # runtime.groot <- melt(as.data.table(runtime.groot), "InputSize") # colnames(runtime.groot) <- c("Input.Size","Iteration","Elapsed.Time") # # #--- Plot runtime results # cls <- c("#69b3a2",adjustcolor("#69b3a2", alpha=0.5)) # gg1 <- ggplot(runtime.preprocess, aes(x=Input.Size, y=Elapsed.Time)) + # geom_smooth(method=loess, se=TRUE) + # geom_point(color=cls[1], fill=cls[2], size=3, shape=21) + # scale_x_continuous(breaks=pretty(runtime.preprocess$Input.Size)) + # scale_y_continuous(breaks=pretty(runtime.preprocess$Elapsed.Time)) + # theme_pander() + labs(title="groot.preprocess()") + # xlab("Input size (n)") + ylab("Elapsed time (s)") + # theme(aspect.ratio=1, plot.title=element_text(size=12)) # gg2 <- ggplot(runtime.groot, aes(x=Input.Size, y=Elapsed.Time)) + # geom_smooth(method=loess, se=TRUE) + # geom_point(color=cls[1], fill=cls[2], size=3, shape=21) + # scale_x_continuous(breaks=pretty(runtime.groot$Input.Size)) + # scale_y_continuous(breaks=pretty(runtime.groot$Elapsed.Time)) + # theme_pander() + labs(title="groot()") + # xlab("Input size (n)") + ylab("Elapsed time (s)") + # theme(aspect.ratio=1, plot.title=element_text(size=12)) # grid.arrange(gg1, gg2, nrow = 1) # # pdf(file = "rooting_runtime.pdf", width = 7, height = 3) # # grid.arrange(gg1, gg2, nrow = 1) # # dev.off() ## ----label='Session information', eval=TRUE, echo=FALSE----------------------- sessionInfo()