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Multi-site Assessment of Methods for Cell Preservation Upstream of Single Cell RNA Sequencing

GSE329418 Homo sapiens (human) Single-cell RNA-seq 25 samples Submitted 2026/06/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 25 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
25 samples: 25 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
Multisite Assessment of Methods for Cell Preservation Upstream of Single-Cell RNA SequencingJournal of biomolecular techniques : JBT · 2026
Summary (written by the submitters)
Single cell RNA sequencing (scRNA-seq) is a revolutionary technique to identify cell types and their molecular phenotype in heterogeneous biological specimens. ScRNA-seq typically requires fresh, high quality single cell suspensions that are processed immediately to preserve their molecular profiles. This presents a challenge for samples with long preparation times and prevents collection at remote sites lacking the required instrumentation for sample processing.
Read the full summary ↓
Recently, several commercial assays have been released that enable sample preservation at the time of collection either via fixation or cryopreservation, allowing for sample processing to occur months after the initial collection. The Association of Biomolecular Research Facilities’ (ABRF) DNA Sequencing (DSRG) and Genomics Bioinformatics (GBiRG) Research Groups have undertaken a cross-platform, multi-site study to assess the performance and reproducibility of three platforms: a) 10x Genomics FLEX, b) Parse Bioscience Evercode WT v2 and c) Honeycomb Bio HIVE. Total leukocytes were isolated from a single healthy individual using the EasySep RBC depletion reagent. Cells were then characterized by collecting a 21-color flow cytometry dataset for reference and the remaining material was used for scRNA-seq procedures where different sites then processed either the fixed or cryopreserved cells for each method. We evaluated performance of each method across traditional scRNA-seq quality control metrics and analysis applications, including gene/transcript detection sensitivity, cell type discovery and annotation, and differential expression. We demonstrate that data from the methods tested can be effectively integrated and produce concordant results with regard to cell type annotation and relative abundance, though we observe platform-specific differences in the expression of a subset of genes. Preservation-based methods also show better retention of fragile granulocyte populations compared with fresh samples processed using the 10x 3’ workflow. The improvements to preservation methods are changing the way research is conducted and our thorough investigation into the performance of each method provides a valuable resource to help scientists determine the most appropriate single cell preservation workflow given their sample collection logistics and laboratory infrastructure constraints.
Published in
Multisite Assessment of Methods for Cell Preservation Upstream of Single-Cell RNA Sequencing
Kolling Iv FW, Podnar JW, Wilkins O et al. · Journal of biomolecular techniques : JBT 2026 · PMID 42281660 · doi:10.7171/001c.162768
This dataset
Open GSE329418 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 GSE329418_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 PRJNA1458839 and SRA study SRP695753. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42281660) ↗
Study design
25 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 25 sample titles: 25 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
Datasets on a similar topic

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