Single cell RNA sequencing monitoring the development of allogeneic HSC-derived CAR-engineered NKT cells
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 5 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE241996_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1010939 and SRA study SRP457656. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 5 replicated groups read from 10 sample titles; they account for 10 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM7747432 WK1_BI WK1_BI
- GSM7747433 WK2_BI WK2_BI
- GSM7747434 WK3_BI WK3_BI
- GSM7747435 WK4_BI WK4_BI
- GSM7747436 WK5_BI WK5_BI
- GSM7747437 WK1_BI15 WK1_BI
- GSM7747438 WK2_BI15 WK2_BI
- GSM7747439 WK3_BI15 WK3_BI
- GSM7747440 WK4_BI15 WK4_BI
- GSM7747441 WK5_BI15 WK5_BI
- GSE270820 Single cell RNA sequencing to study the in vivo behaviour of allogeneic HSC-derived MCAR-engineered NKT cells 30 samples shares nkt, car-engineered, hsc-derived, allogeneic
- GSE241998 Single cell RNA sequencing to study the in vivo behaviour of allogeneic HSC-derived CAR-engineered NKT cells 9 samples shares nkt, car-engineered, hsc-derived, allogeneic
- GSE294754 MiNK-215: Allogeneic FAP-CAR-IL15 iNKT therapy remodels tumor stroma to enhance anti-tumor immunity 4 samples shares nkt, allogeneic
- GSE270430 Allogeneic HSPC-engineered CD33-targeting CAR-NKT cells synergize with hypomethylating agents for effective and safe treatment of myeloid malignancies 4 samples shares nkt, allogeneic
- GSE304213 Targeting Triple-Negative Breast Cancer Using Allogeneic Stem Cell-Engineered Mesothelin-Specific CAR-NKT Cells with Potent Antitumor Activity 1 samples shares nkt, allogeneic
- GSE290757 Allogeneic iPSC-derived iNKT cells in recurrent head and neck cancer: a phase 1 trial 18 samples shares nkt, allogeneic
- GSE261557 Single cell resolution analysis of multi-tissue derived human iNKT cells reveals novel transcriptional paradigms 3 samples shares nkt
- GSE311015 amplicon sequence analysis of iPSC-derived iNKT cells and primary iNKT cells 18 samples shares nkt
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.