### R code from vignette source 'exampleFingerprint.Rnw' ### Encoding: UTF-8 ################################################### ### code chunk number 1: exampleFingerprint.Rnw:28-33 ################################################### options(width=60, stringsAsFactors = FALSE) options(continue=" ") tpbEnv <- new.env() assign("cat", function(file,...) cat(file=stderr(),...), tpbEnv) environment(txtProgressBar) <- tpbEnv ################################################### ### code chunk number 2: data ################################################### library(GEOquery) GSE26946 <- getGEO("GSE26946") GSE26946.exprs <- exprs(GSE26946[[1]]) GSE26946.exprs[1:5, 1:3] GSE26946.platform <- annotation(GSE26946[[1]]) GSE26946.species <- as.character(unique(phenoData(GSE26946[[1]])$organism_ch1)) GSE26946.names <- as.character(phenoData(GSE26946[[1]])$title) ################################################### ### code chunk number 3: fingerprint ################################################### library(pathprint) library(SummarizedExperiment) library(pathprintGEOData) # load the data data(SummarizedExperimentGEO) # load("chipframe.rda") ds = c("chipframe", "genesets","pathprint.Hs.gs","platform.thresholds","pluripotents.frame") data(list = ds) # extract part of the GEO.fingerprint.matrix and GEO.metadata.matrix GEO.fingerprint.matrix = assays(geo_sum_data[,300000:350000])$fingerprint GEO.metadata.matrix = colData(geo_sum_data[,300000:350000]) # free up space by removing the geo_sum_data object remove(geo_sum_data) # Extract common GSMs since we only loaded part of the geo_sum_data object common_GSMs <- intersect(pluripotents.frame$GSM,colnames(GEO.fingerprint.matrix)) GSE26946.fingerprint <- exprs2fingerprint(exprs = GSE26946.exprs, platform = GSE26946.platform, species = GSE26946.species, progressBar = FALSE ) GSE26946.fingerprint[1:5, 1:3] ################################################### ### code chunk number 4: existingFingerprint ################################################### colnames(GSE26946.exprs) %in% colnames(GEO.fingerprint.matrix) GSE26946.existing <- GEO.fingerprint.matrix[,colnames(GSE26946.exprs)] all.equal(GSE26946.existing, GSE26946.fingerprint) ################################################### ### code chunk number 5: heatmap ################################################### heatmap(GSE26946.fingerprint[apply(GSE26946.fingerprint, 1, sd) > 0, ], labCol = GSE26946.names, mar = c(10,10), col = c("blue", "white", "red")) ################################################### ### code chunk number 6: plotheatmap ################################################### heatmap(GSE26946.fingerprint[apply(GSE26946.fingerprint, 1, sd) > 0, ], labCol = GSE26946.names, mar = c(10,10), col = c("blue", "white", "red")) ################################################### ### code chunk number 7: pluripotent ################################################### # construct pluripotent consensus pluripotent.consensus<-consensusFingerprint( GEO.fingerprint.matrix[,common_GSMs], threshold=0.9) # calculate distance from the pluripotent consensus for all arrays geo.pluripotentDistance<-consensusDistance( pluripotent.consensus, GEO.fingerprint.matrix) # calculate distance from pluripotent consensus for GSE26946 arrays GSE26946.pluripotentDistance<-consensusDistance( pluripotent.consensus, GSE26946.fingerprint) ################################################### ### code chunk number 8: histogram ################################################### par(mfcol = c(2,1), mar = c(0, 4, 4, 2)) geo.pluripotentDistance.hist<-hist(geo.pluripotentDistance[,"distance"], nclass = 50, xlim = c(0,1), main = "Distance from pluripotent consensus") par(mar = c(7, 4, 4, 2)) hist(geo.pluripotentDistance[pluripotents.frame$GSM, "distance"], breaks = geo.pluripotentDistance.hist$breaks, xlim = c(0,1), main = "", xlab = "") hist(GSE26946.pluripotentDistance[, "distance"], breaks = geo.pluripotentDistance.hist$breaks, xlim = c(0,1), main = "", col = "red", add = TRUE) ################################################### ### code chunk number 9: plothistogram ################################################### par(mfcol = c(2,1), mar = c(0, 4, 4, 2)) geo.pluripotentDistance.hist<-hist(geo.pluripotentDistance[,"distance"], nclass = 50, xlim = c(0,1), main = "Distance from pluripotent consensus") par(mar = c(7, 4, 4, 2)) hist(geo.pluripotentDistance[pluripotents.frame$GSM, "distance"], breaks = geo.pluripotentDistance.hist$breaks, xlim = c(0,1), main = "", xlab = "") hist(GSE26946.pluripotentDistance[, "distance"], breaks = geo.pluripotentDistance.hist$breaks, xlim = c(0,1), main = "", col = "red", add = TRUE) ################################################### ### code chunk number 10: distance ################################################### GSE26946.H1<-consensusFingerprint( GSE26946.fingerprint[,grep("H1", GSE26946.names)], threshold=0.9) geo.H1Distance<-consensusDistance( GSE26946.H1, GEO.fingerprint.matrix) # look at top 20 GEO.metadata.matrix[match(head(rownames(geo.H1Distance),20), rownames(GEO.metadata.matrix)), c("GSE", "GPL", "Source")]