Bulk RNA-seq analysis of IFNγ-PD-L1all, IFNγ+PD-L1all and IFNγ+PD-L1hi PDAC cells
RNA-seq (gene expression) · mouse · 10 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 10 samples: 4 × IFNγ-PD-L1all vs 3 × IFNγ+PD-L1all vs 3 × IFNγ+PD-L1hiGroups 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.
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 GSE222222_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA918823 and SRA study SRP416183. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 3 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.
- GSM6918154 IFNγ-PD-L1all_1 IFNγ-PD-L1all
- GSM6918155 IFNγ-PD-L1all_2 IFNγ-PD-L1all
- GSM6918156 IFNγ-PD-L1all_3 IFNγ-PD-L1all
- GSM6918157 IFNγ-PD-L1all_4 IFNγ-PD-L1all
- GSM6918158 IFNγ+PD-L1all_1 IFNγ+PD-L1all
- GSM6918159 IFNγ+PD-L1all_2 IFNγ+PD-L1all
- GSM6918160 IFNγ+PD-L1all_3 IFNγ+PD-L1all
- GSM6918161 IFNγ+PD-L1hi_1 IFNγ+PD-L1hi
- GSM6918162 IFNγ+PD-L1hi_2 IFNγ+PD-L1hi
- GSM6918163 IFNγ+PD-L1hi_3 IFNγ+PD-L1hi
- GSE297743 APOE3-R136S mutation confers resilience against tau pathology via cGAS-STING-IFN inhibition [bulk RNA-seq] 28 samples shares ifn, rna-seq, bulk
- GSE232196 Differential expression gene signature between primary tumors and metastatic tumors in PDAC and BC mouse models [Bulk Tissue RNA-Seq] 20 samples shares pdac, rna-seq, bulk
- GSE316194 Bulk RNA-seq of WNT-responsive and WNT-secreting cancer cell populations from orthotopic PDAC tumors 16 samples shares pdac, rna-seq, bulk
- GSE263080 RNA-sea of Smad4 wild-type or Smad4 knockout KPC PDAC organoids from monocultures or co-cultures with pancreatic stellate cells and RNA-seq of flow-sorted PSCs from the same co-cultures. 44 samples shares pdac, rna-seq
- GSE263081 RNA-sea of Smad4 wild-type or Smad4 knockout KvPC PDAC organoids from monocultures or co-cultures with pancreatic stellate cells and RNA-seq of flow-sorted PSCs from the same co-cultures. 35 samples shares pdac, rna-seq
- GSE313732 Type I IFN Dynamics Orchestrate Protective ICAM1⁺ Neutrophil Heterogeneity as an Early Checkpoint for Survival in Lethal Viral Infection [RNA-Seq] 78 samples shares ifn, rna-seq
- GSE309564 IFNg shapes macrophage inflammatory responses by STAT1 isoform-specific epigenetic and transcriptional mechanisms [RNA-Seq] 72 samples shares ifn, rna-seq
- GSE298786 Type I IFN impedes early bacterial control in TB-resistant and -susceptible mice and activates neutrophils to restrict lung macrophage-T cell interactions [RNA-seq] 70 samples shares ifn, 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.