## ----maits_load, message=FALSE, warning=FALSE------------------------------ suppressPackageStartupMessages({library(MAST) library(singleCellTK) library(xtable)}) data(maits, package="MAST") maits_sce <- createSCE(assayFile = t(maits$expressionmat)， annotFile = maits$cdat, featureFile = maits$fdat, assayName =" logtpm"， inputDataFrames = TRUE, createLogCounts =FALSE) rm(maits) ## ----maits_summarize，结果= ' asis '--------------------------------------- knitr:: kable (summarizeTable (maits_sce useAssay = " logtpm ")) ## ---- maits_colnames -------------------------------------------------------- colnames (colData (maits_sce)表(colData (maits_sce) ourfilter美元)# #——maits_filter ---------------------------------------------------------- maits_subset < - maits_sce [colData (maits_sce) $ ourfilter]表(colData (maits_subset) ourfilter美元)# #——maits_filter_table,结果= ' asis '------------------------------------ knitr:: kable (summarizeTable (maits_subset useAssay = " logtpm ")) ## ---- maits_availablereduceddims -------------------------------------------- reducedDims (maits_subset) # #——maits_getpcatsne ------------------------------------------------------ maits_subset < - getPCA (maits_subset useAssay =“logtpm reducedDimName =“PCA_logtpm”)maits_subset < getTSNE (maits_subset useAssay =“logtpm”,reducedDimName = " TSNE_logtpm”)reducedDims (maits_subset) # #——maits_pca ------------------------------------------------------------- plotPCA (maits_subset reducedDimName =“PCA_logtpm colorBy = "状态 ") ## ---- maits_tsne ------------------------------------------------------------ plotTSNE (maits_subset reducedDimName =“TSNE_logtpm colorBy = "状态 ") ## ---- maits_convert_symbols,message=FALSE---------------------------------- suppressPackageStartupMessages({library(org. hs . e.g. .db)}) maits_entrez <- maits_子集maits_子集<- convertGeneIDs(maits_子集，inSymbol = "ENTREZID"， outSymbol = "SYMBOL"， database = "org. hs . e.g. .db") #消除MAST对基因名的混淆:rowData (maits_subset)美元primerid < -零# #——maits_thresh fig.height = 8,消息= FALSE ----------------------------- 阈值< - thresholdGenes (maits_subset useAssay =“logtpm”)标准(mfrow = c(5, 4))情节(阈值)票面(mfrow = c (1,1 )) ## ---- maits_MAST、消息= FALSE --------------------------------------------- mast_results < -桅杆(maits_subset、条件=“条件”,useThresh = TRUE, useAssay = " logtpm ") ## ---- maits_violin fig.height = 8,消息= FALSE ----------------------------- MASTviolin (maits_subset useAssay =“logtpm fcHurdleSig = mast_results threshP = TRUE,条件= "条件 ") ## ---- maits_lm fig.height = 8日消息= FALSE --------------------------------- MASTregression (maits_subset useAssay =“logtpm fcHurdleSig = mast_results threshP = TRUE,条件= "条件 ") ## ---- maits_heatmap --------------------------------------------------------- plotDiffEx (maits_subset useAssay = " logtpm ",条件= "条件",geneList = mast_results基因[1:10],美元annotationColors =“汽车”,displayRowLabels = FALSE, displayColumnLabels = FALSE) # #——maits_gsva消息= FALSE --------------------------------------------- gsvaRes < - gsvaSCE (maits_entrez useAssay =“logtpm”、“MSigDB c2(人类,Entrez ID)”,c(“KEGG_PROTEASOME”、“REACTOME_VIF_MEDIATED_DEGRADATION_OF_APOBEC3G”,“REACTOME_P53_INDEPENDENT_DNA_DAMAGE_RESPONSE”、“BIOCARTA_PROTEASOME_PATHWAY”、“REACTOME_METABOLISM_OF_AMINO_ACIDS”,“reactome_regulation_of_ornithine_trna_aminoacylase”，“REACTOME_STABILIZATION_OF_P53”，“reactome_scf_beta_trcp_mediated_降解_of_emi1”)，parallel_sz =1) set.seed(1234) gsvaPlot(maits_子集，gsvaRes，“Violin”，“condition”)gsvaPlot(maits_子集，gsvaRes，“Heatmap”，“condition”)## ----load_bladderbatch，message=FALSE-------------------------------------- library(bladderbatch) data(bladderdata) dat <- bladderEset pheno <- pData(dat) edata <- exprs(dat) bladder_sctke <- createSCE(assayFile = edata, annotFile = pheno, assayName ="microarray"， inputDataFrames = TRUE, createLogCounts =FALSE) ## ----plot_var_microarray, message=FALSE------------------------------------ plotBatchVariance(bladder_sctke, useAssay="microarray"， batch="batch"， condition =" cancer") ## ----run_combat， message=FALSE--------------------------------------------- assay(bladder_sctke, "combat") <- ComBatSCE(inSCE = bladder_sctke, batch = "batch", useAssay = "microarray", covariates = "cancer") ## ----plot_var_postcombat, message=FALSE------------------------------------ plotBatchVariance(bladder_sctke, useAssay="combat", batch="batch", condition = "cancer") ## ----sessionInfo, echo=FALSE----------------------------------------------- sessionInfo()