## ----global_options, include=FALSE----------------------------------------- knitr::opts_chunk$set(fig.width=6, fig.height=6, fig.path='figures/') ## ----loading, message = FALSE---------------------------------------------- library(biosigner) ## ----diaplasma------------------------------------------------------------- data(diaplasma) ## ----diaplasma_strF-------------------------------------------------------- attach(diaplasma) library(ropls) strF(dataMatrix) strF(sampleMetadata) strF(variableMetadata) ## ----diaplasma_plot-------------------------------------------------------- with(sampleMetadata, plot(age, bmi, cex = 1.5, col = ifelse(type == "T1", "blue", "red"), pch = 16)) legend("topleft", cex = 1.5, legend = paste0("T", 1:2), text.col = c("blue", "red")) ## ----select---------------------------------------------------------------- featureSelVl <- variableMetadata[, "mzmed"] >= 450 & variableMetadata[, "mzmed"] < 500 sum(featureSelVl) dataMatrix <- dataMatrix[, featureSelVl] variableMetadata <- variableMetadata[featureSelVl, ] ## ----biosign--------------------------------------------------------------- set.seed(123) diaSign <- biosign(dataMatrix, sampleMetadata[, "type"], bootI = 5) set.seed(NULL) ## ----boxplot--------------------------------------------------------------- plot(diaSign, typeC = "boxplot") ## ----signature------------------------------------------------------------- variableMetadata[getSignatureLs(diaSign)[["complete"]], ] ## ----train----------------------------------------------------------------- trainVi <- 1:floor(0.8 * nrow(dataMatrix)) testVi <- setdiff(1:nrow(dataMatrix), trainVi) ## ----biosign_train, warning = FALSE---------------------------------------- set.seed(123) diaTrain <- biosign(dataMatrix[trainVi, ], sampleMetadata[trainVi, "type"], bootI = 5) set.seed(NULL) ## ----predict--------------------------------------------------------------- diaFitDF <- predict(diaTrain) ## ----confusion------------------------------------------------------------- lapply(diaFitDF, function(predFc) table(actual = sampleMetadata[trainVi, "type"], predicted = predFc)) ## ----accuracy-------------------------------------------------------------- sapply(diaFitDF, function(predFc) { conf <- table(sampleMetadata[trainVi, "type"], predFc) conf <- sweep(conf, 1, rowSums(conf), "/") round(mean(diag(conf)), 3) }) ## ----getAccuracy----------------------------------------------------------- round(getAccuracyMN(diaTrain)["S", ], 3) ## ----performance----------------------------------------------------------- diaTestDF <- predict(diaTrain, newdata = dataMatrix[testVi, ]) sapply(diaTestDF, function(predFc) { conf <- table(sampleMetadata[testVi, "type"], predFc) conf <- sweep(conf, 1, rowSums(conf), "/") round(mean(diag(conf)), 3) }) ## ----expressionset_code, eval = FALSE, message = FALSE, warning = FALSE---- # library(Biobase) # diaSet <- ExpressionSet(assayData = t(dataMatrix), # phenoData = new("AnnotatedDataFrame", data = sampleMetadata)) # set.seed(123) # biosign(diaSet, "type", bootI = 5) # set.seed(NULL) ## ----detach---------------------------------------------------------------- detach(diaplasma) ## ----sacurine-------------------------------------------------------------- data(sacurine) set.seed(123) ## sacSign <- biosign(sacurine[["dataMatrix"]], sacurine[["sampleMetadata"]][, "gender"], methodVc = "plsda") set.seed(NULL) ## ----biomark, warning = FALSE, message = FALSE----------------------------- library(BioMark) data(SpikePos) group1Vi <- which(SpikePos[["classes"]] %in% c("control", "group1")) appleMN <- SpikePos[["data"]][group1Vi, ] spikeFc <- factor(SpikePos[["classes"]][group1Vi]) annotDF <- SpikePos[["annotation"]] rownames(annotDF) <- colnames(appleMN) ## ----biomark_pca----------------------------------------------------------- biomark.pca <- ropls::opls(appleMN, fig.pdfC = NULL) plot(biomark.pca, parAsColFcVn = spikeFc) ## ----biomark_pls----------------------------------------------------------- biomark.pls <- ropls::opls(appleMN, spikeFc) ## ----apple_biosign, warning = FALSE---------------------------------------- set.seed(123) appleSign <- biosign(appleMN, spikeFc) set.seed(NULL) ## ----annotation------------------------------------------------------------ annotDF <- SpikePos[["annotation"]] rownames(annotDF) <- colnames(appleMN) annotDF[getSignatureLs(appleSign)[["complete"]], c("adduct", "found.in.standards")] ## ----golub_false, warning = FALSE, message = FALSE------------------------- library(golubEsets) data(Golub_Merge) golubMN <- t(exprs(Golub_Merge)) leukemiaFc <- pData(Golub_Merge)[["ALL.AML"]] table(leukemiaFc) varSubVi <- 1501:2000 set.seed(123) golubSign <- biosign(golubMN[, varSubVi], leukemiaFc, methodVc = "svm") set.seed(NULL) ## ----hu6800, warning = FALSE, message = FALSE------------------------------ library(hu6800.db) sapply(getSignatureLs(golubSign)[["complete"]], function(probeC) get(probeC, env = hu6800GENENAME)) ## ----empty, echo = FALSE--------------------------------------------------- rm(list = ls()) ## ----sessionInfo, echo=FALSE----------------------------------------------- sessionInfo()