RANKL inhibits macrophage pro-inflammatory Toll-like receptor 2 and 4 signaling and impairs killing of intracellular bacteria
RNA-seq (gene expression) · mouse · 24 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
- 24 samples: 8 conditions, mostly in triplicateGroups 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
- RANKL inhibits macrophage proinflammatory Toll-like receptor 2 and 4 signaling and impairs killing of intracellular bacteriaImmunoHorizons · 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 GSE325337_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 PRJNA1439724 and SRA study SRP685035. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 24 samples.
How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.
- GSM9600990 4h Mock-Infected 0RANKL rep_1 4h Mock-Infected 0RANKL
- GSM9600991 4h Mock-Infected 0RANKL rep_2 4h Mock-Infected 0RANKL
- GSM9600992 4h Mock-Infected 0RANKL rep_3 4h Mock-Infected 0RANKL
- GSM9600993 4h Mock-Infected 100RANKL rep_1 4h Mock-Infected 100RAN…
- GSM9600994 4h Mock-Infected 100RANKL rep_2 4h Mock-Infected 100RAN…
- GSM9600995 4h Mock-Infected 100RANKL rep_3 4h Mock-Infected 100RAN…
- GSM9600996 24h Mock-Infected 0RANKL rep_1 24h Mock-Infected 0RANKL
- GSM9600997 24h Mock-Infected 0RANKL rep_2 24h Mock-Infected 0RANKL
- GSM9600998 24h Mock-Infected 0RANKL rep_3 24h Mock-Infected 0RANKL
- GSM9600999 24h Mock-Infected 100RANKL rep_1 24h Mock-Infected 100RA…
- GSM9601000 24h Mock-Infected 100RANKL rep_2 24h Mock-Infected 100RA…
- GSM9601001 24h Mock-Infected 100RANKL rep_3 24h Mock-Infected 100RA…
- GSM9601002 4h STm-Infected 0RANKL rep_1 4h STm-Infected 0RANKL
- GSM9601003 4h STm-Infected 0RANKL rep_2 4h STm-Infected 0RANKL
- GSM9601004 4h STm-Infected 0RANKL rep_3 4h STm-Infected 0RANKL
- GSM9601005 4h STm-Infected 100RANKL rep_1 4h STm-Infected 100RANKL
- GSM9601006 4h STm-Infected 100RANKL rep_2 4h STm-Infected 100RANKL
- GSM9601007 4h STm-Infected 100RANKL rep_3 4h STm-Infected 100RANKL
- GSM9601008 24h STm-Infected 0RANKL rep_1 24h STm-Infected 0RANKL
- GSM9601009 24h STm-Infected 0RANKL rep_2 24h STm-Infected 0RANKL
- GSM9601010 24h STm-Infected 0RANKL rep_3 24h STm-Infected 0RANKL
- GSM9601011 24h STm-Infected 100RANKL rep_1 24h STm-Infected 100RAN…
- GSM9601012 24h STm-Infected 100RANKL rep_2 24h STm-Infected 100RAN…
- GSM9601013 24h STm-Infected 100RANKL rep_3 24h STm-Infected 100RAN…
- GSE309415 Bile acid receptor Tgr5 prevents macrophage hyperinflammation during bacterial sepsis through metabolic and epigenetic silencing 12 samples shares macrophage, receptor, bacteria
- GSE250551 Targeting inflammation with chimeric antigen receptor macrophages using a signal switch 32 samples shares macrophage, receptor
- GSE272424 Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages 6 samples shares macrophage, receptor
- GSE326173 Nuclear receptor Nur77 resolves the inflammatory response of macrophages primarily by regulating expression of AP-1 transcription factors and their target genes [ChIP-seq] 42 samples shares macrophage, receptor
- GSE263895 Both host and parasite non-coding RNAs co-ordinate the regulation of macrophage gene expression to reduce pro-inflammatory immune responses and promote tissue repair pathways during infection with fasciola hepatica 40 samples shares pro-inflammatory, macrophage
- GSE225514 Role of RANKL in mouse intestinal epithelial cells 28 samples shares rankl
- GSE319684 Timecourse of FACS sorted Ly6C+ monocytes, tissue resident alveolar macrophages (trAMs), monocyte derived alveolar macrophages (bmAMs) and epithelial cells from SARS-CoV-2 (maVie16) vs. IAV (PR8) infected mouse lungs 176 samples shares macrophage
- GSE269191 ZEB2 is a Master Switch Controlling the Tumor-Associated Macrophage Program [in vivo] 145 samples shares macrophage
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.