scSorter.R
In scSorter: Implementation of 'scSorter' Algorithm

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

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library(scSorter)

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load(url('https://github.com/hyguo2/scSorter/blob/master/inst/extdata/TMpancreas.RData?raw=true'))

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expr[1:5, 1:5]
dim(expr)

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head(anno)

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topgenes = xfindvariable_genes(expr, ngenes = 2000)

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expr = xnormalize_scData(expr)

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topgene_filter = rowSums(as.matrix(expr)[topgenes, ]!=0) > ncol(expr)*.1
topgenes = topgenes[topgene_filter]

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picked_genes = unique(c(anno$Marker, topgenes))
expr = expr[rownames(expr) %in% picked_genes, ]

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#library(Seurat)
#expr_obj = CreateSeuratObject(expr)
#expr_obj <- NormalizeData(expr_obj, normalization.method = "LogNormalize", scale.factor = 10000, verbose = F)

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#expr_obj <- FindVariableFeatures(expr_obj, selection.method = "vst", nfeatures = 2000, verbose = F)
#topgenes <- head(VariableFeatures(expr_obj), 2000)

#expr = GetAssayData(expr_obj)
#topgene_filter = rowSums(as.matrix(expr)[topgenes, ]!=0) > ncol(expr)*.1
#topgenes = topgenes[topgene_filter]

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#picked_genes = unique(c(anno$Marker, topgenes))
#expr = expr[rownames(expr) %in% picked_genes, ]

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rts <- scSorter(expr, anno)

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print(table(rts$Pred_Type))

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mis_rate = 1 - mean(rts$Pred_Type == true_type)
round(mis_rate, 4)

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table(true_type, rts$Pred_Type)