Revealing an unconventional JAK1/2-STAT3 branch in macrophage IFNγ signaling [RNA-Seq]
RNA-seq (gene expression) · mouse · 30 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
- 30 samples: 15 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.
- Paper
- Revealing an unconventional JAK1/2-STAT3 branch in macrophage IFN-γ signalingCell reports · 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 GSE304588_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 PRJNA1301842 and SRA study SRP606853. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 30 samples.
How we read this: 15 replicated groups read from 30 sample titles; they account for 30 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.
- GSM9153533 STAT1WT_Ctrl_2h_rep1 STAT1WT_Ctrl_2h
- GSM9153534 STAT1WT_Ctrl_2h_rep2 STAT1WT_Ctrl_2h
- GSM9153535 STAT1WT_IFNg_2h_rep1 STAT1WT_IFNg_2h
- GSM9153536 STAT1WT_IFNg_2h_rep2 STAT1WT_IFNg_2h
- GSM9153537 STAT1KO_Ctrl_2h_rep1 STAT1KO_Ctrl_2h
- GSM9153538 STAT1KO_Ctrl_2h_rep2 STAT1KO_Ctrl_2h
- GSM9153539 STAT1KO_IFNg_2h_rep1 STAT1KO_IFNg_2h
- GSM9153540 STAT1KO_IFNg_2h_rep2 STAT1KO_IFNg_2h
- GSM9153541 STAT3WT_Ctrl_2h_rep1 STAT3WT_Ctrl_2h
- GSM9153542 STAT3WT_Ctrl_2h_rep2 STAT3WT_Ctrl_2h
- GSM9153543 STAT3WT_IFNg_2h_rep1 STAT3WT_IFNg_2h
- GSM9153544 STAT3WT_IFNg_2h_rep2 STAT3WT_IFNg_2h
- GSM9153545 STAT3KO_Ctrl_2h_rep1 STAT3KO_Ctrl_2h
- GSM9153546 STAT3KO_Ctrl_2h_rep2 STAT3KO_Ctrl_2h
- GSM9153547 STAT3KO_IFNg_2h_rep1 STAT3KO_IFNg_2h
- GSM9153548 STAT3KO_IFNg_2h_rep2 STAT3KO_IFNg_2h
- GSM9153549 WT_Ctrl_2h_rep1 WT_Ctrl_2h
- GSM9153550 WT_Ctrl_2h_rep2 WT_Ctrl_2h
- GSM9153551 WT_IFNg_2h_rep1 WT_IFNg_2h
- GSM9153552 WT_IFNg_2h_rep2 WT_IFNg_2h
- GSM9153553 WT_IL6_2h_rep1 WT_IL6_2h
- GSM9153554 WT_IL6_2h_rep2 WT_IL6_2h
- GSM9336788 Ctrl_2h_rep1 Ctrl_2h
- GSM9336789 Ctrl_2h_rep2 Ctrl_2h
- GSM9336790 IL6_IFNy_2h_rep1 IL6_IFNy_2h
- GSM9336791 IL6_IFNy_2h_rep2 IL6_IFNy_2h
- GSM9336792 hIL6_2h_rep3 hIL6_2h
- GSM9336793 hIL6_2h_rep4 hIL6_2h
- GSM9336794 IFNy_2h_rep3 IFNy_2h
- GSM9336795 IFNy_2h_rep4 IFNy_2h
- GSE304589 Revealing an unconventional JAK1/2-STAT3 branch in macrophage IFNγ signaling [ChIP-Seq] 16 samples shares 2-stat3, jak1, ifn, unconventional, macrophage, revealing, branch
- GSE309564 IFNg shapes macrophage inflammatory responses by STAT1 isoform-specific epigenetic and transcriptional mechanisms [RNA-Seq] 72 samples shares ifn, macrophage, 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, macrophage, rna-seq
- GSE304155 HE4 regulates anticancer immune evasion by upregulating PD-L1 expression on macrophages through the IFN-γR-STAT3 axis [LLC tumors, scRNA-seq] 6 samples shares ifn, macrophage, 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
- GSE301965 Type I IFN impedes early bacterial control in TB-resistant and -susceptible mice and activates neutrophils to restrict lung macrophage-T cell interactions 72 samples shares ifn, macrophage
- GSE288606 Neurons undergo IFNγ-driven persistent epigenetic shifts and synaptic remodeling in the inflamed brain [RNA-Seq] 52 samples shares ifn, rna-seq
- GSE231931 RNA-seq analysis of B cells cultured with LPS and IL-12 and/or IFN gamma 42 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.