Bulk and single-cell transcriptomics identify gene signatures of stem cell-derived NK cell donors with superior anti-tumor activity
Single-cell RNA-seq · human · 17 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
- 17 samples: 9 × I20-1188 vs 4 × I19-1290 vs 3 × I19-1278Groups 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.
- Paper
- Bulk and single-cell transcriptomics identify gene signatures of stem cell-derived NK cell donors with superior cytolytic activityMolecular therapy. Oncology · 2024
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 GSE249992_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 PRJNA1051570 and SRA study SRP477565. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 3 replicated groups read from 17 sample titles; they account for 16 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.
- GSM7968663 multiplexed samples
- GSM7968664 I20-1188-36 I20-1188
- GSM7968665 I20-1188-34 I20-1188
- GSM7968666 I20-1188-32 I20-1188
- GSM7968667 I20-1188-35 I20-1188
- GSM7968668 I20-1188-33 I20-1188
- GSM7968669 I20-1188-37 I20-1188
- GSM7968670 I20-1188-40 I20-1188
- GSM7968671 I20-1188-38 I20-1188
- GSM7968672 I20-1188-39 I20-1188
- GSM7968673 I19-1290-05 I19-1290
- GSM7968674 I19-1290-04 I19-1290
- GSM7968675 I19-1290-02 I19-1290
- GSM7968676 I19-1278-42 I19-1278
- GSM7968677 I19-1278-44 I19-1278
- GSM7968678 I19-1278-40 I19-1278
- GSM7968679 I19-1290-06 I19-1290
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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.