Evidence map›Paper›PMID 39675380›Full record

ArticleNucleic acids research2025

A comprehensive analysis framework for evaluating commercial single-cell RNA sequencing technologies.

Marco De Simone, Jonathan Hoover, Julia Lau, Hayley M Bennett, Bing Wu, Cynthia Chen, Hari Menon, Amelia Au-Yeung, Sean Lear, Samir Vaidya and 9 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Dissecting Normal and Abnormal Human Kidney Development Using Multiomics.Journal of the American Society of Nephrology : JASN · 2026
    Review
  10. Article
  11. Review
  12. Genome-wide single-cell perturbation screens with VIPerturb-seq.bioRxiv : the preprint server for biology · 2026
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Marco De SimoneDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Jonathan HooverDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.ORCID 0000-0002-2893-4425
Julia LauDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Hayley M BennettDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Bing WuDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Cynthia ChenDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Hari MenonDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Amelia Au-YeungDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Sean LearDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Samir VaidyaDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Minyi ShiDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Jessica M LundDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Ana Xavier-MagalhãesDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Yuxin LiangDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Ahmet KurdogluDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
William E O'GormanDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Zora ModrusanDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.
Daniel LeDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.ORCID 0009-0008-1338-410X
Spyros DarmanisDepartment of Proteomic and Genomic Technologies, Genentech, South San Francisco, 94080, CA, USA.

Funding

Genentech
6 · The paper itself

Abstract

This study examined nine prominent commercially available single-cell RNA sequencing (scRNA-seq) kits across four technology groups. Each kit was characterized using peripheral blood mononuclear cells (PBMCs) from a single donor, which enabled consistent assessment of factors such as analytical performance, protocol duration and cost. The Chromium Fixed RNA Profiling kit from 10× Genomics, with its probe-based RNA detection method, demonstrated the best overall performance. The Rhapsody WTA kit from Becton Dickinson exhibited a balance between performance and cost. Importantly, we introduce the read utilization metric, which differentiates scRNA-seq kits based on the efficiency of converting sequencing reads into usable counts. Thus, read utilization is an important feature that substantially impacts sensitivity and cost. With data from 169, 262 cells, our work provides a comprehensive comparison of commercial scRNA-seq technologies to facilitate the effective implementation of single-cell studies.

Indexed as

Sequence Analysis, RNASingle-Cell AnalysisHumansLeukocytes, MononuclearRNARNA

Identifiers

PMID39675380
PMCPMC11754665

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.