A platelet transcriptomic signature of thromboinflammation predicts cardiovascular risk
RNA-seq (gene expression) · human · 38 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
- 38 samples: 38 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
- A platelet transcriptomic signature of thromboinflammation predicts cardiovascular riskJCI insight · 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 GSE308951_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 PRJNA1333481 and SRA study SRP625636. 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 38 sample titles: 38 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.
- GSM9256675 CRD001, baseline visit
- GSM9256676 CRD002, baseline visit
- GSM9256677 CRD003, baseline visit
- GSM9256678 CRD005, baseline visit
- GSM9256679 CRD006, baseline visit
- GSM9256680 CRD007, baseline visit
- GSM9256681 CRD010, baseline visit
- GSM9256682 CRD013, baseline visit
- GSM9256683 CRD014, baseline visit
- GSM9256684 CRD018, baseline visit
- GSM9256685 CRD021, baseline visit
- GSM9256686 CRD023, baseline visit
- GSM9256687 CRD025, baseline visit
- GSM9256688 CRD028, baseline visit
- GSM9256689 CRD032, baseline visit
- GSM9256690 CRD033, baseline visit
- GSM9256691 CRD037, baseline visit
- GSM9256692 CRD038, baseline visit
- GSM9256693 CRD046, baseline visit
- GSM9256694 CRD048, baseline visit
- GSM9256695 CRD060, baseline visit
- GSM9256696 CRD061, baseline visit
- GSM9256697 CRD062, baseline visit
- GSM9256698 CRD063, baseline visit
- GSM9256699 CRD064, baseline visit
- GSM9256700 CRD065, baseline visit
- GSM9256701 CRD067, baseline visit
- GSM9256702 CRD068, baseline visit
- GSM9256703 CRD070, baseline visit
- GSM9256704 CRD071, baseline visit
- GSM9256705 CRD074, baseline visit
- GSM9256706 CRD076, baseline visit
- GSM9256707 CRD083, baseline visit
- GSM9256708 CRD089, baseline visit
- GSM9256709 CRD099, baseline visit
- GSM9256710 CRD104, baseline visit
- GSM9256711 CRD111, baseline visit
- GSM9256712 CRD114, baseline visit
- GSE232027 Platelet Reactivity ExpreSsion Score Predicts Cardiovascular Risk 84 samples shares cardiovascular, platelet, predicts, risk
- GSE312011 A transcriptomic signature that predicts pre-hypertension in adolescence and higher systolic blood pressure in childhood 31 samples shares signature, predicts
- GSE269335 Single-cell multimodal profiling of monocytes reveals diverse phenotypes and alterations linked to cardiovascular disease risks 118 samples shares cardiovascular, risk
- GSE312780 Blood-flow restriction resistance training improves skeletal muscle mitochondrial oxidative capacity and cardiovascular risk factors in type 2 diabetes 34 samples shares cardiovascular, risk
- GSE296830 Investigation of transcriptomic signatures associated with sepsis risk in patients with infection 32 samples shares signature, risk
- GSE286042 Transcriptomic and Proteomic Signatures Following AS03-adjuvanted Influenza A/H7N9 Vaccine 1232 samples shares signature
- GSE280113 Progenitor effects and unique transcriptomic signatures linked to differentiation phenotype in clonally expanded antigen-specific CD8 T memory stem cells (TSCM) 509 samples shares signature
- GSE336577 Integrated Transcriptomic and Immune Analysis Reveals Distinct Mitochondrial and Immune Signature in COVID-19 ARDS Requiring Invasive Mechanical Ventilation 94 samples shares signature
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.