Spatial and cell type specific molecular genetic investigations of inflammatory myopathies with selective perifascicular injury.
RNA-seq (gene expression) · human · 301 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
- 301 samples: 27 conditions, mostly with about 12 replicates eachGroups 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
- Lupus myositis, a type I interferon driven necrotizing myopathy with regional heterogeneityResearch square · 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 GSE330891_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 PRJNA1465874 and SRA study SRP700352. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 301 samples.
How we read this: 27 replicated groups read from 301 sample titles; they account for 301 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.
- GSM9734828 DSP-1001660014456-Z-A02 DSP-1001660014456-Z-A
- GSM9734829 DSP-1001660014456-Z-A03 DSP-1001660014456-Z-A
- GSM9734830 DSP-1001660014456-Z-A04 DSP-1001660014456-Z-A
- GSM9734831 DSP-1001660014456-Z-A05 DSP-1001660014456-Z-A
- GSM9734832 DSP-1001660014456-Z-A06 DSP-1001660014456-Z-A
- GSM9734833 DSP-1001660014456-Z-A07 DSP-1001660014456-Z-A
- GSM9734834 DSP-1001660014456-Z-A08 DSP-1001660014456-Z-A
- GSM9734835 DSP-1001660014456-Z-A09 DSP-1001660014456-Z-A
- GSM9734836 DSP-1001660014456-Z-A10 DSP-1001660014456-Z-A
- GSM9734837 DSP-1001660014456-Z-A11 DSP-1001660014456-Z-A
- GSM9734838 DSP-1001660014456-Z-A12 DSP-1001660014456-Z-A
- GSM9734839 DSP-1001660014456-Z-B01 DSP-1001660014456-Z-B
- GSM9734840 DSP-1001660014456-Z-B02 DSP-1001660014456-Z-B
- GSM9734841 DSP-1001660014456-Z-B03 DSP-1001660014456-Z-B
- GSM9734842 DSP-1001660014456-Z-B04 DSP-1001660014456-Z-B
- GSM9734843 DSP-1001660014456-Z-B05 DSP-1001660014456-Z-B
- GSM9734844 DSP-1001660014456-Z-B06 DSP-1001660014456-Z-B
- GSM9734845 DSP-1001660014456-Z-B07 DSP-1001660014456-Z-B
- GSM9734846 DSP-1001660014456-Z-B08 DSP-1001660014456-Z-B
- GSM9734847 DSP-1001660014456-Z-B09 DSP-1001660014456-Z-B
- GSM9734848 DSP-1001660014456-Z-B10 DSP-1001660014456-Z-B
- GSM9734849 DSP-1001660014456-Z-B11 DSP-1001660014456-Z-B
- GSM9734850 DSP-1001660014456-Z-B12 DSP-1001660014456-Z-B
- GSM9734851 DSP-1001660014456-Z-C01 DSP-1001660014456-Z-C
- GSM9734852 DSP-1001660014456-Z-C02 DSP-1001660014456-Z-C
- GSM9734853 DSP-1001660014456-Z-C03 DSP-1001660014456-Z-C
- GSM9734854 DSP-1001660014456-Z-C04 DSP-1001660014456-Z-C
- GSM9734855 DSP-1001660014456-Z-C05 DSP-1001660014456-Z-C
- GSM9734856 DSP-1001660014456-Z-C06 DSP-1001660014456-Z-C
- GSM9734857 DSP-1001660014456-Z-C07 DSP-1001660014456-Z-C
- GSM9734858 DSP-1001660014456-Z-C08 DSP-1001660014456-Z-C
- GSM9734859 DSP-1001660014456-Z-C09 DSP-1001660014456-Z-C
- GSM9734860 DSP-1001660014456-Z-C10 DSP-1001660014456-Z-C
- GSM9734861 DSP-1001660014456-Z-C11 DSP-1001660014456-Z-C
- GSM9734862 DSP-1001660014456-Z-C12 DSP-1001660014456-Z-C
- GSM9734863 DSP-1001660014456-Z-D01 DSP-1001660014456-Z-D
- GSM9734864 DSP-1001660014456-Z-D02 DSP-1001660014456-Z-D
- GSM9734865 DSP-1001660014456-Z-D03 DSP-1001660014456-Z-D
- GSM9734866 DSP-1001660014456-Z-D04 DSP-1001660014456-Z-D
- GSM9734867 DSP-1001660014456-Z-D05 DSP-1001660014456-Z-D
+ 261 more — browse all 301 samples with per-sample file links →
- GSE331197 Spatial and cell type specific molecular genetic investigations of inflammatory myopathies with selective perifascicular injury [RNA] 300 samples shares investigations, perifascicular, myopathies, selective, specific, spatial, genetic, injury
- GSE278317 Protect and shield strategy of reactive acyl glucuronides licenses precision-omics investigations into drug-induced liver injury 63 samples shares investigations, injury
- GSE273492 Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [RNA-Seq] 36 samples shares selective, genetic
- GSE312389 Delineating the role of co-stimulatory signals on human virus-specific memory CD8+ T cell activation and expansion using highly selective T cell receptor-targeted biologics 20 samples shares selective, specific
- GSE273490 Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [CUT&Run] 120 samples shares selective, genetic
- GSE275721 Lineage master regulator and cancer-selective partner transcription factors rewire 3D genome topology for tumor-specific gene control 72 samples shares selective, specific
- GSE264444 Sequencing-Guided Design of Genetically Encoded Small RNAs Targeting CAG Repeats for Selective Inhibition of Mutant Huntingtin 41 samples shares selective, genetic
- GSE275657 Selective identification of epigenetic regulators at methylated genomic sites by SelectID [ChIP-seq] 14 samples shares selective, genetic
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.