GEO series

Plasma membrane order maps functional diversity in immune cells

GSE341300 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2026/09/09 Platform GPL30173

At a glance

Single-cell RNA-seq · human · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 14 samples: 14 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.

Summary (written by the submitters)

Cell membranes undergo biophysical remodelling as an adaptation to the surroundings and to perform specific biological functions. However, the extent and relevance of such changes in human immune cells remain unknown, largely due to the lack of single-cell and multidimensional methodologies. Here, we apply a cytometry-based method to fill this gap by combining biophysical profiling with simultaneous analysis of immune cell markers.

Read the full summary ↓

This platform reveals notable cell type-dependent plasma membrane order heterogeneity in immune cells. By sorting immune cells according to their membrane order and performing transcriptome and spatial surface proteome analyses together with functional tests, we show that plasma membrane order can be used to identify subsets of immune cells with distinct phenotypes and functional behaviours. Our findings demonstrate a broad heterogeneity of plasma membrane order in immune cells that will provide a more precise definition of immune cell states based on their biophysical properties in health and disease.

This dataset

Open GSE341300 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 GSE341300_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1501296. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

14 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 14 sample titles: 14 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

GSM9903400 Donor D, Low Plasma Membrane Order
GSM9903401 Donor D, High Plasma Membrane Order
GSM9903402 Donor E, Low Plasma Membrane Order
GSM9903403 Donor E, High Plasma Membrane Order
GSM9903404 Donor F, Low Plasma Membrane Order
GSM9903405 Donor F, High Plasma Membrane Order
GSM9903406 Donor K, Low Plasma Membrane Order
GSM9903407 Donor K, High Plasma Membrane Order
GSM9903408 Donor L, Low Plasma Membrane Order
GSM9903409 Donor L, High Plasma Membrane Order
GSM9903410 Donor M, Low Plasma Membrane Order
GSM9903411 Donor M, High Plasma Membrane Order
GSM9903412 Donor N, Low Plasma Membrane Order
GSM9903413 Donor N, High Plasma Membrane Order

Datasets on a similar topic

GSE330969 Ninjurins 1 Regulate Hematopoietic Stem Cell Amplification Through Canonical WNT Signaling Independently of Plasma Membrane Rupture Activity 16 samples shares membrane, plasma
GSE294455 Sphingolipids in extracellular vesicles released from the skeletal muscle plasma membrane control muscle stem cell fate during muscle regeneration 10 samples shares membrane, plasma
GSE308521 Phosphatidylserine and RhoB connect phosphatidylinositol 4-phosphate and phosphatidic acid metabolism at the plasma membrane 12 samples shares membrane, plasma
GSE254707 Single-cell transcriptomic analysis identifies infiltrating plasmacytoid dendritic cells in psoriasis epidermis 4988 samples shares plasma
GSE313527 Plasma Extracellular Vesicle Modulate Immune Cell Transcriptional Responses Following Acute Myocardial Infarction 74 samples shares plasma
GSE296680 Using plasma cell-free mRNA to profile immune response and myocardial damage in immune checkpoint inhibitor-induced myocarditis 26 samples shares plasma
GSE235832 Piezoeletric cold atmospheric plasma sensitizes head and neck cancer to chemotherapy and immune checkpoint blockade therapy 24 samples shares plasma
GSE316497 Genotype-Epigenome-Phenotype Integration Reveals the Contributions of Peripheral Immune Cells to Bipolar Disorder Pathogenesis, Phenotypic Heterogeneity, and Therapy 1012 samples shares order

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.