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

knitr::opts_chunk$set(echo = TRUE)
suppressMessages(library(sc2marker))
suppressMessages(library(Seurat))
devtools::install_github('satijalab/seurat-data')
suppressMessages(library(SeuratData))

load data

You can load the HCA-BM object by SeuratData.

#load reference data
InstallData("bmcite")
bmc <- LoadData(ds = "bmcite")
Idents(bmc) <- "celltype.l1"
table([e-mail])

Markers 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(bmc, id = "NK", category = "Flow", org = "human", min.pct = 0.1)
get_antibody(nk.markers, org = "human")

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

Markers for B cell

b.markers <- Detect_single_marker(bmc, id = "B cell", category = "Flow", org = "human", min.pct = 0.1)
get_antibody(b.markers, org = "human")

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

Markers for T cell

t.markers <- Detect_single_marker(bmc, id = "T cell", category = "Flow", org = "human", min.pct = 0.1)
get_antibody(t.markers, org = "human")

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

Markers for Progenitor cells

Prog.markers <- Detect_single_marker(bmc, id = "Progenitor cells", category = "Flow", org = "human", min.pct = 0.1)
get_antibody(Prog.markers, org = "human")

# Ridge plot of top 9 markers of Progenitor cells
plot_ridge(bmc, id = "Progenitor cells", genes = Prog.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

Markers for Mono/DC

Mono.markers <- Detect_single_marker(bmc, id = "Mono/DC", category = "Flow", org = "human", min.pct = 0.1)
get_antibody(Mono.markers, org = "human")

# Ridge plot of top 9 markers of Mono cells
plot_ridge(bmc, id = "Mono/DC", genes = Mono.markers[1:9,]$gene, ncol = 3, assay = "RNA", aggr.other = F)

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