Retrotransposons in Werner syndrome-derived macrophages trigger type I interferon-dependent inflammation in an atherosclerosis model [RTE RNA-seq]
RNA-seq (gene expression) · human · 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
- Homo sapiens (human)
- 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
- Retrotransposons in Werner syndrome-derived macrophages trigger type I interferon-dependent inflammation in an atherosclerosis modelNature communications · 2024
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 GSE247721_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 PRJNA1040212 and SRA study SRP471853. 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.
- GSM7899343 Healthy, iMac, oxLDL, neg, 1 Healthy, iMac, oxLDL, n…
- GSM7899344 Healthy, iMac, oxLDL, neg, 2 Healthy, iMac, oxLDL, n…
- GSM7899345 Healthy, iMac, oxLDL, neg, 3 Healthy, iMac, oxLDL, n…
- GSM7899346 WS, iMac, oxLDL, neg,1 WS, iMac, oxLDL, neg,
- GSM7899347 WS, iMac, oxLDL, neg, 2 WS, iMac, oxLDL, neg,
- GSM7899348 WS, iMac, oxLDL, neg, 3 WS, iMac, oxLDL, neg,
- GSM7899349 WS, iMac, oxLDL, neg, 4 WS, iMac, oxLDL, neg,
- GSM7899350 gcWS, iMac, oxLDL, neg,1 gcWS, iMac, oxLDL, neg,
- GSM7899351 gcWS, iMac, oxLDL, neg, 2 gcWS, iMac, oxLDL, neg,
- GSM7899352 gcWS, iMac, oxLDL, neg, 3 gcWS, iMac, oxLDL, neg,
- GSM7899353 Healthy, iMac, oxLDL, pos, 1 Healthy, iMac, oxLDL, p…
- GSM7899354 Healthy, iMac, oxLDL, pos, 2 Healthy, iMac, oxLDL, p…
- GSM7899355 Healthy, iMac, oxLDL, pos, 3 Healthy, iMac, oxLDL, p…
- GSM7899356 WS, iMac, oxLDL, pos,1 WS, iMac, oxLDL, pos,
- GSM7899357 WS, iMac, oxLDL, pos, 2 WS, iMac, oxLDL, pos,
- GSM7899358 WS, iMac, oxLDL, pos, 3 WS, iMac, oxLDL, pos,
- GSM7899359 WS, iMac, oxLDL, pos, 4 WS, iMac, oxLDL, pos,
- GSM7899360 gcWS, iMac, oxLDL, pos,1 gcWS, iMac, oxLDL, pos,
- GSM7899361 gcWS, iMac, oxLDL, pos, 2 gcWS, iMac, oxLDL, pos,
- GSM7899362 gcWS, iMac, oxLDL, pos, 3 gcWS, iMac, oxLDL, pos,
- GSM7899363 Healthy, PB-Mac, 1 Healthy, PB-Mac,
- GSM7899364 Healthy, PB-Mac, 2 Healthy, PB-Mac,
- GSM7899365 WS, PB-Mac, 1 WS, PB-Mac,
- GSM7899366 WS, PB-Mac, 2 WS, PB-Mac,
- GSE247718 Retrotransposons in Werner syndrome-derived macrophages trigger type I interferon-dependent inflammation in an atherosclerosis model [VSMC RNA-seq] 12 samples shares interferon-dependent, retrotransposons, syndrome-derived, atherosclerosis, macrophages, trigger, rna-seq
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares rte, rna-seq
- GSE252020 Decoding CD4+ T cell transcriptome in giant cell arteritis: novel pathways and altered cross-talk with monocytes [RNA-seq] 98 samples shares rte, rna-seq
- GSE339038 RNA-Seq of CD3+ T cells flow sorted from MLR assays with TNF/TNFR inhibitory compound combination treatments 64 samples shares rte, rna-seq
- GSE335924 RNA-seq Identifies FOS as a Potential Therapeutic Target Activating Neural Stem Cells via miR-21/SOX2 Pathway in Hypertensive Intracerebral Hemorrhage 53 samples shares rte, rna-seq
- GSE289574 Multi-omics Analysis of Skeletal Muscle Identifies Dysregulation of Hypoxia-Induced Genes in Peripheral Artery Disease [RNA-seq] 40 samples shares rte, rna-seq
- GSE339456 Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [RNA-seq] 35 samples shares rte, rna-seq
- GSE287651 Cell-type specific profiling of human entorhinal cortex at the onset of Alzheimer’s disease neuropathology [RNA-seq] 15 samples shares rte, 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.