Evidence map›Paper›PMID 41503158›Full record

ArticleNAR genomics and bioinformatics2026

Evaluating the practical aspects and performance of commercial single-cell RNA sequencing technologies.

Anna E Elz, Derrik Gratz, Annalyssa Long, David Sowerby, Azi Hadadianpour, Evan W Newell

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Anna E ElzFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.ORCID https://orcid.org/0000-0002-7718-3015
Derrik GratzFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.ORCID https://orcid.org/0009-0002-5934-576X
Annalyssa LongFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.
David SowerbyFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.
Azi HadadianpourFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.
Evan W NewellFred Hutch Innovation Lab, Immunotherapy Integrated Research Center, Fred Hutchinson Cancer Center, Seattle, WA 98109, United States.ORCID https://orcid.org/0000-0002-2889-243X

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
VIRUS-MEDIATED MYELOSUPPRESSIONP01CA018029 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI STEPHANIE J LEE · 1985 to 2026
$128.4M
Systems Biology CoreU19AI128914 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI Margaret Juliana McElrath, KENNETH D STUART · 2017 to 2026
$29.5M
Understand & overcome resistance to PD-1P01CA225517 · NCI · UNIVERSITY OF WASHINGTON · PI Cecilia C Yeung · 2019 to 2026
$22.7M
The roles of EBV-specific T cells in response to checkpoint blockade immunotherapy of EBV-driven nasopharyngeal carcinomaR01CA264646 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI NEWELL, EVAN · 2021 to 2025
$3.0M
NCI NIH HHS P01 CA018029NCI NIH HHS P01 CA225517NCI NIH HHS P30 CA015704NCI NIH HHS R01 CA264646NIAID NIH HHS U19 AI128914
6 · The paper itself

Abstract

The rapid development of updated and new commercially available single-cell transcriptomics platforms provides users with a range of experimental options. Cost, sensitivity, throughput, flexibility, and ease of use all influence the selection of an optimal workflow. We performed a comprehensive comparison of single-cell transcriptomic approaches using multiple standardized PBMCs from different donors. We report on standard single-cell metrics, including cell recovery, sequencing efficiency, sensitivity, cell annotation, and differential gene expression for seven recently available kits that interrogate whole transcriptome mRNA, and two that incorporate TCR profiling. We also discuss workflow throughput, sample requirements, timing, cost, and labor as critical factors to consider. Apart from the platform-specific experimental constraints, our findings highlight how differences in cell recovery and sensitivity influence the ability to resolve niche cell subtypes such as CD4 + and CD8 + T-cells. Platforms with higher intra-sample variation had reduced sequencing efficiency, which cumulatively impacts reproducibility and overall experiment cost. By including TCR chain recovery for multiple donors, we provide the first comparison of T-cell specific performance in the only assays available for single cell TCR recovery. This work provides a basis by which users can balance performance and practical considerations when selecting a single-cell RNA sequencing platform.

Indexed as

Sequence Analysis, RNASingle-Cell AnalysisGene Expression ProfilingHumansReceptors, Antigen, T-CellReproducibility of ResultsSingle-Cell Gene Expression AnalysisTranscriptomeReceptors, Antigen, T-Cell

Identifiers

PMID41503158
PMCPMC12770963

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.