## ----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) ropls::view(dataMatrix) ropls::view(sampleMetadata, standardizeL = TRUE) ropls::view(variableMetadata, standardizeL = TRUE) ## ----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------------------------------------------------------------------ diaSign <- biosigner::biosign(dataMatrix, sampleMetadata[, "type"], bootI = 5) ## ----boxplot------------------------------------------------------------------ biosigner::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------------------------------------------- diaTrain <- biosigner::biosign(dataMatrix[trainVi, ], sampleMetadata[trainVi, "type"], bootI = 5) ## ----predict------------------------------------------------------------------ diaFitDF <- biosigner::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(biosigner::getAccuracyMN(diaTrain)["S", ], 3) ## ----performance-------------------------------------------------------------- diaTestDF <- biosigner::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, warning = FALSE, message = FALSE--------------------- library(Biobase) diaSet <- Biobase::ExpressionSet(assayData = t(dataMatrix), phenoData = new("AnnotatedDataFrame", data = sampleMetadata), featureData = new("AnnotatedDataFrame", data = variableMetadata)) ropls::view(diaSet) biosigner::biosign(diaSet, "type", bootI = 5) ## ----view_ExpressionSet------------------------------------------------------- ropls::view(diaSet) ## ----detach------------------------------------------------------------------- detach(diaplasma) ## ----sacurine----------------------------------------------------------------- data(sacurine) sacSign <- biosigner::biosign(sacurine[["dataMatrix"]], sacurine[["sampleMetadata"]][, "gender"], methodVc = "plsda") ## ----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 = "none") ropls::plot(biomark.pca, parAsColFcVn = spikeFc) ## ----biomark_pls-------------------------------------------------------------- biomark.pls <- ropls::opls(appleMN, spikeFc) ## ----apple_biosign, warning = FALSE------------------------------------------- appleSign <- biosigner::biosign(appleMN, spikeFc) ## ----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 golubSign <- biosigner::biosign(golubMN[, varSubVi], leukemiaFc, methodVc = "svm") ## ----hu6800, warning = FALSE, message = FALSE--------------------------------- library(hu6800.db) sapply(biosigner::getSignatureLs(golubSign)[["complete"]], function(probeC) get(probeC, env = hu6800GENENAME)) ## ----empty, echo = FALSE------------------------------------------------------ rm(list = ls()) ## ----sessionInfo, echo=FALSE-------------------------------------------------- sessionInfo()