Getting Start with De Novo CIDER (dnCIDER)
Source:vignettes/dnCIDER_highlevel.Rmd
dnCIDER_highlevel.RmdLoad pancreas data
The example data can be downloaded from https://figshare.com/s/d5474749ca8c711cc205.
Pancreatic cell data1 contain cells from human (8241 cells) and mouse (1886 cells).
load("../data/pancreas_counts.RData") # count matrix
load("../data/pancreas_meta.RData") # meta data/cell information
seu <- CreateSeuratObject(counts = pancreas_counts, meta.data = pancreas_meta)
table(seu$Batch)
#>
#> human mouse
#> 8241 1886Perform dnCIDER (high-level)
DnCIDER contains three steps
seu <- initialClustering(seu, additional.vars.to.regress = "Sample", dims = 1:15)
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ider <- getIDEr(seu, downsampling.size = 35, use.parallel = FALSE, verbose = FALSE)
seu <- finalClustering(seu, ider, cutree.h = 0.35) # final clusteringVisualise clustering results
We use the Seurat pipeline to perform normalisation
(NormalizeData), preprocessing
(FindVariableFeatures and ScaleData) and
dimension reduction (RunPCA and RunTSNE).
seu <- NormalizeData(seu, verbose = FALSE)
seu <- FindVariableFeatures(seu, selection.method = "vst", nfeatures = 2000, verbose = FALSE)
seu <- ScaleData(seu, verbose = FALSE)
seu <- RunPCA(seu, npcs = 20, verbose = FALSE)
seu <- RunTSNE(seu, reduction = "pca", dims = 1:12)We can see
scatterPlot(seu, "tsne", colour.by = "CIDER_cluster", title = "asCIDER clustering results") 
By comparing the dnCIDER results to the cell annotation from the publication1, we observe that dnCIDER correctly identify the majority of populations across two species.
scatterPlot(seu, "tsne", colour.by = "Group", title = "Ground truth of cell populations") 
Technical
sessionInfo()
#> R version 4.1.2 (2021-11-01)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] parallel stats graphics grDevices utils datasets methods
#> [8] base
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#> other attached packages:
#> [1] cowplot_1.1.1 SeuratObject_4.0.4 Seurat_4.1.0 CIDER_0.99.1
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