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welch-lab / liger

R package for integrating and analyzing multiple single-cell datasets
GNU General Public License v3.0
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Subsetting integrated seurat object and reclustering using liger #276

Closed Prathyusha-konda closed 1 year ago

Prathyusha-konda commented 2 years ago

Hi, I have an integrated seurat object from 6 datasets from which I want to subset specific clusters and recluster using liger. I would like to know if there is a recommended workflow for this.

Should I split the integrated seurat and rerun the entire pipeline? (from this tutorial - https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/liger.html)

Does it matter if the seurat object was originally integrated with liger or logNormalize or SCT?

Thanks in advance for your suggestions!

ifnb <- NormalizeData(ifnb) ifnb <- FindVariableFeatures(ifnb) ifnb <- ScaleData(ifnb, split.by = "stim", do.center = FALSE) ifnb <- RunOptimizeALS(ifnb, k = 20, lambda = 5, split.by = "stim") ifnb <- RunQuantileNorm(ifnb, split.by = "stim") ifnb <- FindNeighbors(ifnb, reduction = "iNMF", dims = 1:20) ifnb <- FindClusters(ifnb, resolution = 0.55) ifnb <- RunUMAP(ifnb, dims = 1:ncol(ifnb[["iNMF"]]), reduction = "iNMF")

cgao90 commented 2 years ago

Hi, we would suggest subsetting the cells in the clusters of interest and running the entire LIGER pipeline (start with the count data).