## ----scTensor with NCBI Gene ID, eval=FALSE----------------------------------- # library("scTensor") # library("AnnotationHub") # library("LRBaseDbi") # # # Input matrix # input <- ... # sce <- SingleCellExperiment(assays=list(counts = input)) # # Celltype vector # label <- ... # # LRBase.XXX.eg.db # ah <- AnnotationHub() # dbfile <- query(ah, c("LRBaseDb", "Homo sapiens", "v002"))[[1]] # LRBase.Hsa.eg.db <- LRBaseDbi::LRBaseDb(dbfile) # # Setting # cellCellSetting(sce, LRBase.Hsa.eg.db, label) ## ----Seurat, eval=FALSE------------------------------------------------------- # if(!require(Seurat)){ # BiocManager::install("Seurat") # library(Seurat) # } # # # Load the PBMC dataset # pbmc.data <- Read10X(data.dir = "filtered_gene_bc_matrices/hg19/") # # # Initialize the Seurat object with the raw (non-normalized data). # pbmc <- CreateSeuratObject(counts = pbmc.data, # project = "pbmc3k", min.cells = 3, min.features = 200) ## ----Ensembl with Organism DB, echo=TRUE-------------------------------------- suppressPackageStartupMessages(library("scTensor")) if(!require(Homo.sapiens)){ BiocManager::install("Homo.sapiens") suppressPackageStartupMessages(library(Homo.sapiens)) } if(!require(scTGIF)){ BiocManager::install("scTGIF") suppressPackageStartupMessages(library(scTGIF)) } # 1. Input matrix input <- matrix(1:20, nrow=4, ncol=5) # 2. Gene identifier in each row rowID <- c("ENSG00000204531", "ENSG00000181449", "ENSG00000136997", "ENSG00000136826") # 3. Corresponding table LefttoRight <- select(Homo.sapiens, column=c("ENSEMBL", "ENTREZID"), keytype="ENSEMBL", keys=rowID) # ID conversion (input <- convertRowID(input, rowID, LefttoRight)) ## ----Ensembl with AnnotationHub, echo=TRUE------------------------------------ suppressPackageStartupMessages(library("AnnotationHub")) # 1. Input matrix input <- matrix(1:20, nrow=4, ncol=5) # 3. Corresponding table ah <- AnnotationHub() # Database of Human hs <- query(ah, c("OrgDb", "Homo sapiens"))[[1]] LefttoRight <- select(hs, column=c("ENSEMBL", "ENTREZID"), keytype="ENSEMBL", keys=rowID) (input <- convertRowID(input, rowID, LefttoRight)) ## ----Gene Symbol with Organism DB, echo=TRUE---------------------------------- # 1. Input matrix input <- matrix(1:20, nrow=4, ncol=5) # 2. Gene identifier in each row rowID <- c("POU5F1", "SOX2", "MYC", "KLF4") # 3. Corresponding table LefttoRight <- select(Homo.sapiens, column=c("SYMBOL", "ENTREZID"), keytype="SYMBOL", keys=rowID) # ID conversion (input <- convertRowID(input, rowID, LefttoRight)) ## ----Gene Symbol with AnnotationHub, echo=TRUE-------------------------------- # 1. Input matrix input <- matrix(1:20, nrow=4, ncol=5) # 3. Corresponding table ah <- AnnotationHub() # Database of Human hs <- query(ah, c("OrgDb", "Homo sapiens"))[[1]] LefttoRight <- select(hs, column=c("SYMBOL", "ENTREZID"), keytype="SYMBOL", keys=rowID) (input <- convertRowID(input, rowID, LefttoRight)) ## ----Seurat normalization, eval=FALSE----------------------------------------- # pbmc2 <- NormalizeData(pbmc, normalization.method = "LogNormalize", # scale.factor = 10000) # sce <- as.SingleCellExperiment(pbmc2) # assayNames(sce) # counts, logcounts ## ----Scater normalization, eval=FALSE----------------------------------------- # if(!require(scater)){ # BiocManager::install("scater") # library(scater) # } # sce <- SingleCellExperiment(assays=list(counts = input)) # cpm(sce) <- calculateCPM(sce) # sce <- normalize(sce) # assayNames(sce) # counts, normcounts, logcounts, cpm ## ----Original normalization, eval=FALSE--------------------------------------- # # User's Original Normalization Function # CPMED <- function(input){ # libsize <- colSums(input) # median(libsize) * t(t(input) / libsize) # } # # Normalization # normcounts(sce) <- log10(CPMED(counts(sce)) + 1) ## ----sessionInfo, echo=FALSE-------------------------------------------------- sessionInfo()