Transcriptomic differences in RXRαβ-deficient and WT alveolar macrophages using the CD11c-Cre+ mouse model (RNA-Seq)
RNA-seq (gene expression) · mouse · 11 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
- 11 samples: 4 × mAM_KO vs 4 × mAM_WT vs 3 × Imm_KOGroups 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 GSE243160_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 PRJNA1016455 and SRA study SRP460330. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 11 samples.
How we read this: 3 replicated groups read from 11 sample titles; they account for 11 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.
- GSM7780058 Imm_KO2 Imm_KO
- GSM7780059 Imm_KO3 Imm_KO
- GSM7780060 Imm_KO4 Imm_KO
- GSM7780061 mAM_KO1 mAM_KO
- GSM7780062 mAM_KO2 mAM_KO
- GSM7780063 mAM_KO3 mAM_KO
- GSM7780064 mAM_KO4 mAM_KO
- GSM7780065 mAM_WT1 mAM_WT
- GSM7780066 mAM_WT2 mAM_WT
- GSM7780067 mAM_WT3 mAM_WT
- GSM7780068 mAM_WT4 mAM_WT
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- GSE325329 Transcriptomic profiling of macrophages that phagocytosed apoptotic Treg or conventional CD4⁺ T (Tconv) cells under different polarization conditions [RNA-Seq] 28 samples shares macrophages, rna-seq
- 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 macrophages, alveolar
- GSE290816 Cell autonomous regional differences in oligodendrocyte precursor cell development and response to oncohistone H3.3 K27M [RNA-seq] 142 samples shares differences, rna-seq
- GSE317613 pH-Responsive Nanostructured Calcium Phosphate Microrods as Pulmonary Delivery Platform: Fabrication, Characterization, and Comparative Assessment of Cytotoxic and Transcriptomic Responses in Alveolar Macrophages 15 samples shares macrophages, alveolar
- 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 macrophages, rna-seq
- GSE284404 Increased cardiac macrophages in Sorbs2-deficient hearts: revealing a potential role for macrophage in responding to embryonic myocardial abnormalities 35 samples shares macrophages, deficient
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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.