Determining the impact of anti-IL6 and anti-OSM on macrophage and fibroblast biology in a model of fibrotic lung disease [NGS3341]
RNA-seq (gene expression) · mouse · 25 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
- 25 samples: 25 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.
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 GSE262966_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 PRJNA1095009 and SRA study SRP499081. 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 25 sample titles: 25 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.
- GSM8182235 BLM_7838 [NGS3341]
- GSM8182236 BLM_7839 [NGS3341]
- GSM8182237 BLM_7840 [NGS3341]
- GSM8182238 BLM_7841 [NGS3341]
- GSM8182239 BLM_7842 [NGS3341]
- GSM8182240 BLM_aIL6_7843 [NGS3341]
- GSM8182241 BLM_aIL6_7844 [NGS3341]
- GSM8182242 BLM_aIL6_7845 [NGS3341]
- GSM8182243 BLM_aIL6_7846 [NGS3341]
- GSM8182244 BLM_aIL6_7847 [NGS3341]
- GSM8182245 BLM_aIL6_aOSM_7853 [NGS3341]
- GSM8182246 BLM_aIL6_aOSM_7854 [NGS3341]
- GSM8182247 BLM_aIL6_aOSM_7855 [NGS3341]
- GSM8182248 BLM_aIL6_aOSM_7856 [NGS3341]
- GSM8182249 BLM_aIL6_aOSM_7857 [NGS3341]
- GSM8182250 BLM_aOSM_7848 [NGS3341]
- GSM8182251 BLM_aOSM_7849 [NGS3341]
- GSM8182252 BLM_aOSM_7850 [NGS3341]
- GSM8182253 BLM_aOSM_7851 [NGS3341]
- GSM8182254 BLM_aOSM_7852 [NGS3341]
- GSM8182255 PBS_7833 [NGS3341]
- GSM8182256 PBS_7834 [NGS3341]
- GSM8182257 PBS_7835 [NGS3341]
- GSM8182258 PBS_7836 [NGS3341]
- GSM8182259 PBS_7837 [NGS3341]
- 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
- GSE300757 Efferocytosis induces proangiogenic function and chromatin remodeling in tumor-associated macrophages 127 samples shares macrophage
- GSE280003 Gpnmb and Spp1 mark a conserved macrophage injury response masking fibrosis-specific programming in the lung 81 samples shares macrophage
- GSE319035 P21+TREM2+-Senescent Macrophages Fuel Inflammaging and Metabolic Dysfunction-Associated Steatotic Liver Disease [NAFLD_time_course] 77 samples shares macrophage
- GSE280514 Spatially-restricted and ontogenically-distinct hepatic macrophages are required for tissue repair. 48 samples shares macrophage
- GSE268774 Lymph node macrophages drive immune tolerance and resistance to cancer therapy by expression of the immune-regulatory cytokine IL-33 [RNA-seq] 48 samples shares macrophage
- GSE300925 Lyn expression in macrophages promotes TLR activation and restricts proliferation in an isoform-independent manner 48 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.