Integrative Gene and Isoform Co-expression Networks Reveal Regulatory Rewiring in Stress-related Psychiatric Disorders [PBMC]
RNA-seq (gene expression) · human · 299 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
- 299 samples: 299 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.
- Paper
- Integrative gene and isoform co-expression networks reveal regulatory rewiring in stress-related psychiatric disordersiScience · 2025
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 GSE289146_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 PRJNA1221806 and SRA study SRP562912. 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 299 sample titles: 299 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.
- GSM8785021 total RNA-seq from sample MUC23510_S328
- GSM8785022 total RNA-seq from sample MUC23422_S240
- GSM8785023 total RNA-seq from sample MUC23353_S171
- GSM8785024 total RNA-seq from sample MUC23268_S86
- GSM8785025 total RNA-seq from sample MUC23419_S237
- GSM8785026 total RNA-seq from sample MUC23247_S65
- GSM8785027 total RNA-seq from sample MUC23471_S289
- GSM8785028 total RNA-seq from sample MUC23252_S70
- GSM8785029 total RNA-seq from sample MUC23432_S250
- GSM8785030 total RNA-seq from sample MUC23259_S77
- GSM8785031 total RNA-seq from sample MUC23544_S362
- GSM8785032 total RNA-seq from sample MUC23251_S69
- GSM8785033 total RNA-seq from sample MUC23307_S125
- GSM8785034 total RNA-seq from sample MUC23481_S299
- GSM8785035 total RNA-seq from sample MUC23536_S354
- GSM8785036 total RNA-seq from sample MUC23225_S43
- GSM8785037 total RNA-seq from sample MUC23201_S19
- GSM8785038 total RNA-seq from sample MUC23489_S307
- GSM8785039 total RNA-seq from sample MUC23211_S29
- GSM8785040 total RNA-seq from sample MUC23406_S224
- GSM8785041 total RNA-seq from sample MUC23498_S316
- GSM8785042 total RNA-seq from sample MUC23313_S131
- GSM8785043 total RNA-seq from sample MUC23506_S324
- GSM8785044 total RNA-seq from sample MUC23452_S270
- GSM8785045 total RNA-seq from sample MUC23237_S55
- GSM8785046 total RNA-seq from sample MUC23202_S20
- GSM8785047 total RNA-seq from sample MUC23449_S267
- GSM8785048 total RNA-seq from sample MUC23390_S208
- GSM8785049 total RNA-seq from sample MUC23330_S148
- GSM8785050 total RNA-seq from sample MUC23547_S365
- GSM8785051 total RNA-seq from sample MUC23187_S5
- GSM8785052 total RNA-seq from sample MUC23192_S10
- GSM8785053 total RNA-seq from sample MUC23340_S158
- GSM8785054 total RNA-seq from sample MUC23335_S153
- GSM8785055 total RNA-seq from sample MUC23497_S315
- GSM8785056 total RNA-seq from sample MUC23426_S244
- GSM8785057 total RNA-seq from sample MUC23311_S129
- GSM8785058 total RNA-seq from sample MUC23545_S363
- GSM8785059 total RNA-seq from sample MUC23283_S101
- GSM8785060 total RNA-seq from sample MUC23370_S188
+ 259 more — browse all 299 samples with per-sample file links →
- GSE289144 Integrative Gene and Isoform Co-expression Networks Reveal Regulatory Rewiring in Stress-related Psychiatric Disorders [whole blood] 37 samples shares stress-related, co-expression, psychiatric, regulatory, disorders, networks, rewiring
- GSE298578 Single cell RNA profiling of blood CD4+ T cells identifies distinct helper and dysfunctional regulatory clusters in children with SLE (5' PBMC validation dataset) 14 samples shares pbmc, regulatory
- GSE285774 Single cell RNA profiling of blood CD4+ T cells identifies distinct helper and dysfunctional regulatory clusters in children with SLE [PBMCs] 10 samples shares pbmc, regulatory
- GSE268210 Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: Dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling 30 samples shares pbmc, networks
- GSE325907 Placental gene co-expression networks and mediation analysis identifies pathways and genes associated with birthweight 319 samples shares co-expression, networks
- GSE262442 Scaled and efficient derivation of loss-of-function alleles in risk genes for neurodevelopmental and psychiatric disorders in human iPSCs 69 samples shares psychiatric, disorders
- GSE293155 SETD1A Regulates Psychiatric Gene Networks Involved in Genomic Stability and Synaptic Function in Rare and Sporadic Schizophrenia [bulk RNA-seq] 24 samples shares psychiatric, networks
- GSE263809 Chromatin accessibility mapping for functional GWAS risk variants of neuropsychiatric and neurodegenerative disorders in hiPSC-derived neural cells 21 samples shares psychiatric, disorders
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.