LY6D Identifies Persistent Tumor-Initiating Cells Driving Pancreatic Tumorigenesis [RNA-seq]
Single-cell RNA-seq · mouse · 16 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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
- LY6D identifies persistent stem-like cells driving pancreatic tumourigenesisGut · 2026
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 GSE299488_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 PRJNA1274718 and SRA study SRP591285. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. 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.
- GSM9039724 L1EEL270020_KPC1199pxpr_1.R1.raw.fastq.gz
- GSM9039725 L1EEL270021_KPC1199pxpr_2.R1.raw.fastq.gz
- GSM9039726 L1EEL270023_KPC1199pxpr_4.R1.raw.fastq.gz
- GSM9039727 L1EEL270024_KPC1199pxpr_5.R1.raw.fastq.gz
- GSM9039728 L1EEL270025_KPC1199m3_1.R1.raw.fastq.gz
- GSM9039729 L1EEL270027_KPC1199m3_3.R1.raw.fastq.gz
- GSM9039730 L1EEL270028_KPC1199m3_4.R1.raw.fastq.gz
- GSM9039731 L1EEL270029_KPC1199m3_5.R1.raw.fastq.gz
- GSM9039732 pxpr_1_1.fq.gz
- GSM9039733 pxpr_2_1.fq.gz
- GSM9039734 OE_1_1.fq.gz
- GSM9039735 OE_2_1.fq.gz
- GSM9039736 hi_1_1.fq.gz
- GSM9039737 hi_2_1.fq.gz
- GSM9039738 low_1_1.fq.gz
- GSM9039739 low_2_1.fq.gz
- GSE299487 LY6D Identifies Persistent Tumor-Initiating Cells Driving Pancreatic Tumorigenesis [scRNA-seq] 12 samples shares ly6d, tumor-initiating, tumorigenesis, identifies, persistent, pancreatic, driving, rna-seq
- GSE279089 Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis [RNA-Seq] 76 samples shares tumorigenesis, pancreatic, driving, rna-seq
- GSE279088 Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis [ATAC-Seq] 74 samples shares tumorigenesis, pancreatic, driving
- GSE215960 Subclonal evolution revealed by single-cell profiles of expressed mutations identifies adaptation mechanisms to immunotherapy in melanoma [scRNA-seq] 192 samples shares identifies, rna-seq
- GSE299686 Longitudinal liquid biopsy identifies an early predictive biomarker of immune checkpoint blockade response in head and neck squamous cell carcinoma [bulk RNA-seq] 178 samples shares identifies, rna-seq
- GSE293874 Anchored screening identifies transcription factor blueprints underlying dendritic cell diversity and subset-specific anti-tumor immunity [mouse bulk RNA-seq] 167 samples shares identifies, rna-seq
- GSE299683 Longitudinal liquid biopsy identifies an early predictive biomarker of immune checkpoint blockade response in head and neck squamous cell carcinoma [scRNA-seq] 125 samples shares identifies, rna-seq
- GSE98969 Single cell RNA-seq identifies a unique microglia type associated with Alzheimer’s disease [RNA] 97 samples shares identifies, rna-seq
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.