MetaNeighbor.R
In MetaNeighbor: Single cell replicability analysis

## ----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)