In CostaLab/scMarkerDetect: Detect marker panel from scRNA-seq profile

knitr::opts_chunk$set(echo = TRUE)
suppressMessages(library(sc2marker))

load data

mca.spleen
Idents(mca.spleen) <- "anno"
ids <- c("T cell(Spleen)", "Macrophage(Spleen)", "NK cell(Spleen)", "Marginal zone B cell(Spleen)")
[e-mail]$annotation_simplified <- [e-mail]$anno

Simplify the cell annotation

ids <- c("T cell(Spleen)", "Macrophage(Spleen)", "NK cell(Spleen)", "Marginal zone B cell(Spleen)")
[e-mail]$annotation_simplified <- ifelse([e-mail]$annotation_simplified %in% ids,  [e-mail]$annotation_simplified, "Other")
[e-mail]$annotation_simplified[[e-mail]$annotation_simplified == "T cell(Spleen)"] <- "T Cell"
[e-mail]$annotation_simplified[[e-mail]$annotation_simplified == "Marginal zone B cell(Spleen)"] <- "B Cell"
[e-mail]$annotation_simplified[[e-mail]$annotation_simplified == "NK cell(Spleen)"] <- "NK Cell"
[e-mail]$annotation_simplified[[e-mail]$annotation_simplified == "Macrophage(Spleen)"] <- "Macro"
Idents(mca.spleen) <- "annotation_simplified"

Markers identification for NK cell

To run sc2marker you need to execute the following command, providing a clustered single cell data sets (as Seurat object), the cell type of interest and the antibody databased (IHC, ICC or Flow).

nk.markers <- Detect_single_marker(mca.spleen, id = "NK Cell", category = "Flow", org = "mouse", min.pct = 0.1)
get_antibody(nk.markers, org = "mouse")

# Ridge plot of top 9 markers of NK cells
plot_ridge(mca.spleen, id = "NK Cell", genes = nk.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

Markers identification for B cell

b.markers <- Detect_single_marker(mca.spleen, id = "B Cell", category = "Flow", org = "mouse", min.pct = 0.1)
get_antibody(b.markers, org = "mouse")

# Ridge plot of top 9 markers of B cells
plot_ridge(mca.spleen, id = "B Cell", genes = b.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

Markers identification for T cell

t.markers <- Detect_single_marker(mca.spleen, id = "T Cell", category = "Flow", org = "mouse", min.pct = 0.1)
get_antibody(t.markers, org = "mouse")

# Ridge plot of top 9 markers of T cells
plot_ridge(mca.spleen, id = "T Cell", genes = t.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

Markers identification for Macrophages

Macro.markers <- Detect_single_marker(mca.spleen, id = "Macro", category = "Flow", org = "mouse", min.pct = 0.1)
get_antibody(Macro.markers, org = "mouse")

# Ridge plot of top 9 markers of Macrophages
plot_ridge(mca.spleen, id = "Macro", genes = Macro.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

Session Info

sessionInfo()

CostaLab/scMarkerDetect documentation built on May 12, 2022, 6:05 a.m.