This repository contains the R script used to generate the figures based on single-cell RNA-seq data presented in:
**Conti et al., 2025**
*Senescence and inflammation are unintended adverse consequences of CRISPR-Cas9/AAV6 mediated gene editing in hematopoietic stem cells*.
Published in **Cell Reports Medicine**.
## 🔬 Study Context
Single-cell RNA sequencing (scRNA-seq) was used to characterize the transcriptional landscape and cell state dynamics in human hematopoietic stem and progenitor cells (HSPCs) following CRISPR-Cas9/AAV6-mediated gene editing. The aim was to identify specific subpopulations enriched for senescence and inflammatory signatures.
## 📂 Repository Content
-`Figures_scRNA_seq.R`
This R script includes the code used to generate UMAPs, cluster-specific gene expression plots, and pathway enrichment visualizations included in the manuscript. Analyses were performed using Seurat and clusterProfiler, with annotations based on known hematopoietic markers and senescence-associated gene sets.
## 📊 Data Availability
The scRNA-seq dataset is available on GEO under the accession **[GSE244256](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE244256)**.
## 🧰 Tools and Packages Used
-`Seurat` for normalization, dimensionality reduction, clustering and visualization
-`clusterProfiler` for pathway enrichment
-`ggplot2` for figure rendering
## 📌 Citation
If you use this dataset or code, please cite:
> Conti A., Giannetti K., Midena F., et al. (2025).
> *Senescence and inflammation are unintended adverse consequences of CRISPR-Cas9/AAV6 mediated gene editing in hematopoietic stem cells*.
