## ----eval = TRUE, message=FALSE----------------------------------------------- library(MetaNeighbor) library(SummarizedExperiment) data(mn_data) data(GOmouse) ## ----eval=TRUE,fig.width=4,fig.height=3, results='hide'----------------------- AUROC_scores = MetaNeighbor(dat = mn_data, experiment_labels = as.numeric(factor(mn_data$study_id)), celltype_labels = metadata(colData(mn_data))[["cell_labels"]], genesets = GOmouse, bplot = TRUE) ## ----eval= TRUE--------------------------------------------------------------- head(AUROC_scores) ## ----eval = TRUE-------------------------------------------------------------- library(MetaNeighbor) data(mn_data) ## ----eval = TRUE-------------------------------------------------------------- var_genes = variableGenes(dat = mn_data, exp_labels = mn_data$study_id) head(var_genes) ## ----eval = TRUE-------------------------------------------------------------- length(var_genes) ## ----eval=TRUE---------------------------------------------------------------- celltype_NV = MetaNeighborUS(var_genes = var_genes, dat = mn_data, study_id = mn_data$study_id, cell_type = mn_data$cell_type) ## ----eval=TRUE,fig.width=7,fig.height=6.5------------------------------------- cols = rev(colorRampPalette(RColorBrewer::brewer.pal(11,"RdYlBu"))(100)) breaks = seq(0, 1, length=101) gplots::heatmap.2(celltype_NV, margins=c(8,8), keysize=1, key.xlab="AUROC", key.title="NULL", trace = "none", density.info = "none", col = cols, breaks = breaks, offsetRow=0.1, offsetCol=0.1, cexRow = 0.7, cexCol = 0.7) ## ----eval = TRUE-------------------------------------------------------------- top_hits = topHits(cell_NV = celltype_NV, dat = mn_data, study_id = mn_data$study_id, cell_type = mn_data$cell_type, threshold = 0.9) top_hits ## ----eval = TRUE, message=FALSE----------------------------------------------- library(MetaNeighbor) library(SummarizedExperiment) data(mn_data) data(GOmouse) ## ----eval = TRUE,fig.width=4,fig.height=3, results='hide'--------------------- AUROC_scores = MetaNeighbor(dat = mn_data, experiment_labels = as.numeric(factor(mn_data$study_id)), celltype_labels = metadata(colData(mn_data))[["cell_labels"]], genesets = GOmouse, bplot = TRUE, fast_version = TRUE) ## ----eval = TRUE, fig.width = 7, fig.height = 6.5----------------------------- var_genes = variableGenes(dat = mn_data, exp_labels = mn_data$study_id) celltype_NV = MetaNeighborUS(var_genes = var_genes, dat = mn_data, study_id = mn_data$study_id, cell_type = mn_data$cell_type, fast_version = TRUE) cols = rev(colorRampPalette(RColorBrewer::brewer.pal(11,"RdYlBu"))(100)) breaks = seq(0, 1, length=101) gplots::heatmap.2(celltype_NV, margins=c(8,8), keysize=1, key.xlab="AUROC", key.title="NULL", trace = "none", density.info = "none", col = cols, breaks = breaks, offsetRow=0.1, offsetCol=0.1, cexRow = 0.7, cexCol = 0.7) ## ----eval = FALSE, message = FALSE-------------------------------------------- # library(SingleCellExperiment) # library(Matrix) # baron <- readRDS('baron-human.rds') # segerstolpe <- readRDS('segerstolpe.rds') ## ----eval = FALSE------------------------------------------------------------- # common_genes <- intersect(rownames(baron), rownames(segerstolpe)) # baron <- baron[common_genes,] # segerstolpe <- segerstolpe[common_genes, !(segerstolpe$cell_type1 %in% c('not applicable', 'co-expression'))] ## ----eval = FALSE------------------------------------------------------------- # new_colData = data.frame( # study_id = rep(c('baron', 'segerstolpe'), c(ncol(baron), ncol(segerstolpe))), # cell_type = c(as.character(colData(baron)$cell_type1), colData(segerstolpe)$cell_type1) # ) # pancreas <- SingleCellExperiment( # Matrix(cbind(assay(baron, 1), assay(segerstolpe, 1)), sparse = TRUE), # colData = new_colData # ) # dim(pancreas) # rm(baron); rm(segerstolpe) ## ----eval = FALSE, fig.width=7,fig.height=6.5--------------------------------- # var_genes = variableGenes(dat = pancreas, exp_labels = pancreas$study_id) # celltype_NV = MetaNeighborUS(var_genes = var_genes, # dat = pancreas, # study_id = pancreas$study_id, # cell_type = pancreas$cell_type, # fast_version = TRUE) # cols = rev(colorRampPalette(RColorBrewer::brewer.pal(11,"RdYlBu"))(100)) # breaks = seq(0, 1, length=101) # gplots::heatmap.2(celltype_NV, # margins=c(8,8), # keysize=1, # key.xlab="AUROC", # key.title="NULL", # trace = "none", # density.info = "none", # col = cols, # breaks = breaks, # offsetRow=0.1, # offsetCol=0.1, # cexRow = 0.7, # cexCol = 0.7) ## ----eval = FALSE------------------------------------------------------------- # all_pancreas <- readRDS('all_pancreas.rds') # dim(all_pancreas) ## ----eval = FALSE,fig.width=7,fig.height=6.5---------------------------------- # var_genes = variableGenes(dat = all_pancreas, exp_labels = all_pancreas$Study_ID) # celltype_NV = MetaNeighborUS(var_genes = var_genes, # dat = all_pancreas, # study_id = all_pancreas$Study_ID, # cell_type = all_pancreas$Celltype, # fast_version = TRUE) # cols = rev(colorRampPalette(RColorBrewer::brewer.pal(11,"RdYlBu"))(100)) # breaks = seq(0, 1, length=101) # gplots::heatmap.2(celltype_NV, # margins=c(8,8), # keysize=1, # key.xlab="AUROC", # key.title="NULL", # trace = "none", # density.info = "none", # col = cols, # breaks = breaks, # offsetRow=0.1, # offsetCol=0.1, # cexRow = 0.7, # cexCol = 0.7) ## ----eval = FALSE,fig.width=4,fig.height=3, results='hide'-------------------- # data(GOhuman) # small_pancreas = all_pancreas[, all_pancreas$Celltype %in% c('alpha', 'beta', 'delta')] # celltype_matrix = model.matrix(~small_pancreas$Celltype - 1) # colnames(celltype_matrix) = levels(as.factor(small_pancreas$Celltype)) # AUROC_scores = MetaNeighbor(dat = small_pancreas, # experiment_labels = as.numeric(factor(small_pancreas$Study_ID)), # celltype_labels = celltype_matrix, # genesets = GOhuman, # bplot = TRUE, # fast_version = TRUE)