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