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Extracellular Vesicle Online Knowledge Explorer (EVOKE) - A guiding tool for the selection of methods to prepare extracellular vesicles from human biofluids II

GSE302211 Homo sapiens (human) RNA-seq (gene expression) 73 samples Submitted 2026/06/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 73 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
73 samples: 25 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.
Summary (written by the submitters)
Extracellular vesicles (EVs) exert multiple biological functions which has spurred their development as disease biomarkers and drug delivery vehicles. However, the wide range of EV preparation methods and the complexity of biofluids pose significant challenges for reproducible research and clinical translation. To address this difficulty, we developed the Extracellular Vesicle Online Knowledge Explorer (EVOKE)—a pioneering resource designed to assist researchers in evaluating and comparing EV preparation methods.
Read the full summary ↓
To establish EVOKE, an international consortium was formed to systematically compare widely used EV preparation methods across diverse biofluids for key performance metrics using trackable reference materials and complementary characterization methods. EVOKE is the first freely accessible resource (www.evoke-tool.org) that guides researchers towards the informed selection of an optimal EV preparation method for a dedicated study goal, currently powered by over 2.4 million data points and amendable to future developments. It offers crucial insights into method-dependent efficiency, specificity, repeatability, and biomolecular variations and activity, ultimately steering informed method selection and reproducibility. In conclusion, EVOKE provides a strong foundation for coping with methodological challenges and advancing the clinical translation of EV research.
This dataset
Open GSE302211 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE302211_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1289213 and SRA study SRP599713. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
25 conditions, mostly in triplicate
EXO-TotalRNA_Urine_Healthy ×3 EXO-TotalRNA_Urine_Cance ×3 ExoCap_Urine_Healthy ×3 ExoCap_Urine_Cance ×3 ExoSpin_Urine_Cance ×3 ExoSpin_Urine_Healthy ×3 Exosome Purification_Urine_Healthy ×3 exoEasy_Urine_Healthy ×3 +18 more

Supports a between-group comparison across 72 samples.

How we read this: 25 replicated groups read from 73 sample titles; they account for 72 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.

Samples in this study

+ 33 more — browse all 73 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.