The goal of this script is to explore Ptcra expression in our dataset. This gene has been described by Toto et al. (once).

Environment

Libraries

We load the libraries of interest :

library(Seurat)
library(ggplot2)

.libPaths()
## [1] "/shared/home/aonfroy/R/x86_64-conda-linux-gnu-library/4.4"     
## [2] "/shared/ifbstor1/software/miniconda/envs/r-4.4.1/lib/R/library"

Data

We set the directory to load and save data:

data_dir = "/shared/projects/2422_ebaii_n1/atelier_scrnaseq/Intro_Rmd/"

We load data:

sobj = readRDS(paste0(data_dir, "sobj.rds"))
sobj
## An object of class Seurat 
## 12926 features across 200 samples within 1 assay 
## Active assay: RNA (12926 features, 2000 variable features)
##  3 layers present: counts, data, scale.data
##  3 dimensional reductions calculated: pca, harmony, tsne

Analysis

We visualize our favorite gene :

Seurat::FeaturePlot(sobj, reduction = "tsne", features = "Ptcra") +
  ggplot2::theme(aspect.ratio = 1)

Which cells are positive for Ptcra ?

sobj$is_Ptcra_pos = (Seurat::FetchData(sobj, "Ptcra")[, 1] > 0)
head(sobj$is_Ptcra_pos)
## AAACCTGAGACGCTTT.1_1 AAACCTGAGGCATTGG.1_1 AAACCTGGTCAACATC.1_1 
##                FALSE                FALSE                FALSE 
## AAACCTGTCGAGGTAG.1_1 AAACCTGTCGATCCCT.1_1 AAACGGGCACTTACGA.1_1 
##                 TRUE                FALSE                FALSE

We visualize the positive and negative cells :

Seurat::DimPlot(sobj, reduction = "tsne", group.by = "is_Ptcra_pos") +
  ggplot2::theme(aspect.ratio = 1)