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A prospective, international, multisite comparison of platelet isolation techniques for genome-wide transcriptomics: Communication from the SSC of the ISTH

GSE262073 Homo sapiens (human) RNA-seq (gene expression) 114 samples Submitted 2025/03/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 114 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
114 samples: 114 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
Prospective, international, multisite comparison of platelet isolation techniques for genome-wide transcriptomics: communication from the SSC of the ISTHJournal of thrombosis and haemostasis : JTH · 2024
Summary (written by the submitters)
Genome-wide platelet transcriptomics is increasingly being used to uncover new aspects of platelet biology and as a diagnostic and prognostic tool. Nevertheless, platelet isolation methods for transcriptomic studies are not standardized, introducing challenges for cross-study comparisons, data integration, and replication. In this prospective multicenter study, we assessed how three of the most commonly-used platelet isolation protocols influence metrics from next-generation bulk RNA sequencing and functional assays.
Read the full summary ↓
Compared with washing alone, more stringent removal of leukocytes by anti-CD45+ beads or PALL filters resulted in sufficient quantity of RNA for next-generation sequencing and similar quality of RNA sequencing metrics. The more stringent removal of leukocytes resulted in lower relative expression of known leukocyte-specific genes and higher relative expression of known platelet-specific genes. The results were consistent across enrolling sites, suggesting that the techniques are transferrable and reproducible. The use of anti-CD45+ beads reduced integrin aIIbb3 activation to PAR-1 activating peptide (SFLLRN-TRAP) but not ADP, compared to washing alone, while the isolation method had no influence on basal platelet reactivity. In conclusion, genome-wide transcriptional and functional assays in platelets are influenced by isolation technique. These results should help the research community make informed choices about platelet isolation techniques in their own platelet studies.
Published in
Prospective, international, multisite comparison of platelet isolation techniques for genome-wide transcriptomics: communication from the SSC of the ISTH
Banerjee M, Rowley JW, Stubben CJ et al. · Journal of thrombosis and haemostasis : JTH 2024 · PMID 38969303 · doi:10.1016/j.jtha.2024.06.017
This dataset
Open GSE262073 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 GSE262073_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 PRJNA1090123 and SRA study SRP496790. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38969303) ↗
Study design
114 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 114 sample titles: 114 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.

Samples in this study

+ 74 more — browse all 114 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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