chris-mcginnis-ucsf
commented
5 years ago Hello,
Looks to me like the issue arises at this step:
nExp_poi <- round(0.075*length(Gland))
Assuming that 'Gland' is a Seurat object (which it needs to be for the previous commands to work), the length of a Seurat object will be 1. Note in the tutorial I use length(seu_kidney@cell.names), which is the same thing as the total number of cells in the Seurat object. For objects processed using Seurat V3, you'll want to use nrow(Gland@meta.data), since the cell.names slot is no longer used in this package version.
One more note: I use 0.075 to define the expected number of doublets from Poisson statistics (i.e., nExp_poi) because the cell loading density used when creating the kidney data corresponded to a 7.5% doublet formation rate. You will need to adjust this according to the specifics for your dataset.
Let me know if this works, and if it does, please close the issue!
Chris
yuwenjiesail
hridiva
Hi there,
Thank you for sharing this. I tried to use the code provided to analysis my own data and got just one doublet. I am not sure if I have done something wrong but I am not confident about the result. Let me describe my scRNAseq data before hand: About 9000 cells from a type of gland were processed in 10x. Since the tissue is not easy to dissociate, it is expected to have doublets in single-cell samples. I process the scRNAseq data in Seurat v3 (no filtering for potential doublets), and then use the codes below to find doublets
sweep.res.list_Gland <- paramSweep_v3(Gland, PCs = 1:10) sweep.stats_Gland <- summarizeSweep(sweep.res.list_Gland, GT = FALSE) bcmvn_Gland <- find.pK(sweep.stats_Gland) annotations <- Gland@meta.data$RNA_snn_res.0.6 homotypic.prop <- modelHomotypic(annotations) nExp_poi <- round(0.075*length(Gland)) nExp_poi.adj <- round(nExp_poi*(1-homotypic.prop)) Gland <- doubletFinder_v3(Gland, PCs = 1:10, pN = 0.25, pK = 0.09, nExp = nExp_poi, reuse.pANN = FALSE) Gland <- doubletFinder_v3(Gland, PCs = 1:10, pN = 0.25, pK = 0.09, nExp = nExp_poi.adj, reuse.pANN = "pANN_0.25_0.09_0") Gland@meta.data[,"DF_hi.lo"] <- Gland@meta.data$DF.classifications_0.25_0.09_0 Gland@meta.data$DF_hi.lo[which(Gland@meta.data$DF_hi.lo == "Doublet" & Gland@meta.data$DF.classifications_0.25_0.09_0 == "Singlet")] <- "Doublet_lo" Gland@meta.data$DF_hi.lo[which(Gland@meta.data$DF_hi.lo == "Doublet")] <- "Doublet_hi" TSNEPlot(Gland, group.by="DF_hi.lo", plot.order=c("Doublet_hi","Doublet_lo","Singlet"), colors.use=c("black","gold","red"))Here is some output from the code above:Thanks a lot!