Trajectory analysis using Monocle3 with Seurat sub-clustering
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Entering edit mode
13 months ago

Hi all,

I am analyzing single cell RNA-seq data using Seurat and trying to do trajectory analysis using Monocle3. My analysis pipeline is below.

# QC, NormalizeData, FindVariableFeatures for each sample independetly
  SelectIntegrationFeatures > FindIntegrationAnchors > IntegrateData >
  > ScaleData > RunPCA > RunUMAP > FindNeighbors > FindClusters

After then, Sub-clustering and Monocle3 were performed

Oligo <- subset(x, idents=c("OPC", "Oligo1", "Oligo2", "Oligo3")
> RunPCA > RunUMAP > FindNeighbors > FindClusters >
> as.cell_data_set(Oligo) > ~~ > learn_graph > order_cells

Is this the correct way? Or should other processes such as NormalizeData or FindVariableFeatures be performed after subset?

And when sub-clustering (or re-clustering) is performed, the number of clusters is larger than before. Is it correct to perform trajectory analysis after sub-clustering?

Thank you.

Joonhong Kwon

scRNA-seq Trajectory Seurat analysis Monocle3 • 545 views
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