Pathophysiological insights into ACO2-related inherited disorders through combined functional and multi-omic analyses of ACO2 patient-derived fibroblasts
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.
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 GSE332997_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 PRJNA1469605 and SRA study SRP703075. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 6 samples read as cases, 12 as controls.
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.
- GSM9756864 Dominant Optic Atrophy, biol rep 1 Dominant Optic Atrophy,…
- GSM9756865 Dominant Optic Atrophy, biol rep 2 Dominant Optic Atrophy,…
- GSM9756866 Dominant Optic Atrophy, biol rep 3 Dominant Optic Atrophy,…
- GSM9756867 Recessive Optic Atrophy, biol rep 1 Recessive Optic Atrophy…
- GSM9756868 Recessive Optic Atrophy, biol rep 2 Recessive Optic Atrophy…
- GSM9756869 Recessive Optic Atrophy, biol rep 3 Recessive Optic Atrophy…
- GSM9756870 Infantile Cerebellar-Retinal Degeneration, patient 1, biol rep 1 Infantile Cerebellar-Re…
- GSM9756871 Infantile Cerebellar-Retinal Degeneration, patient 1, biol rep 2 Infantile Cerebellar-Re…
- GSM9756872 Infantile Cerebellar-Retinal Degeneration, patient 1, biol rep 3 Infantile Cerebellar-Re…
- GSM9756873 Infantile Cerebellar-Retinal Degeneration, patient 2, biol rep 1 Infantile Cerebellar-Re…
- GSM9756874 Infantile Cerebellar-Retinal Degeneration, patient 2, biol rep 2 Infantile Cerebellar-Re…
- GSM9756875 Infantile Cerebellar-Retinal Degeneration, patient 2, biol rep 3 Infantile Cerebellar-Re…
- GSM9756876 Control 1, biol rep 1 Control 1, biol
- GSM9756877 Control 1, biol rep 2 Control 1, biol
- GSM9756878 Control 1, biol rep 3 Control 1, biol
- GSM9756879 Control 2, biol rep 1 Control 2, biol
- GSM9756880 Control 2, biol rep 2 Control 2, biol
- GSM9756881 Control 2, biol rep 3 Control 2, biol
- GSM9756882 Control 3, biol rep 1 Control 3, biol
- GSM9756883 Control 3, biol rep 2 Control 3, biol
- GSM9756884 Control 3, biol rep 3 Control 3, biol
- GSM9756885 Control 4, biol rep 1 Control 4, biol
- GSM9756886 Control 4, biol rep 2 Control 4, biol
- GSM9756887 Control 4, biol rep 3 Control 4, biol
- GSE317901 Unraveling cetuximab response in head and neck cancer with APHRODYTHE, a multi-omics patient-derived xenograft platform 114 samples shares patient-derived, multi-omic
- GSE316337 Multi-omics profiling reveals microbiota, metabolite, lipid, and immunological heterogeneity underlying distinct pathophysiological mechanisms of age-related endotypes in type 1 diabetes 54 samples shares pathophysiological, multi-omic
- GSE243400 Gene expression profile at single cell level of human Caco2 (hCaco2) cells expressing mouse CD300lf (mCD300lf) infected with murine norovirus (MNV) 12 samples shares aco2
- GSE269372 Microprotein-Encoding RNA Regulation in Cells Treated with Pro-inflammatory and Pro-Fibrotic Stimuli (RNA-Seq Caco2) 12 samples shares aco2
- GSE307568 Patient-derived organoid – immune cell co-culture platform for therapeutics discovery in high-grade endometrial cancer 189 samples shares patient-derived
- GSE300985 A standardized patient-derived glioblastoma organoid platform for evaluating radiotherapy efficacy and overcoming resistance 147 samples shares patient-derived
- GSE334033 A Patient-Derived Xenograft Model Identifies AK1 as a Key Regulator of Metastatic Potential in Primary Triple-Negative Breast Cancer 105 samples shares patient-derived
- GSE288179 Differential response of patient-derived intestinal organoids to site-specific mucosal bacteria in pediatric inflammatory bowel disease 105 samples shares patient-derived
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.