Evidence map›Paper›PMID 35837267›Full record

ArticleJournal of biomolecular techniques : JBT2021

Comparative Analysis of Single-Cell RNA Sequencing Platforms and Methods.

John M Ashton, Hubert Rehrauer, Jason Myers, Jacqueline Myers, Michelle Zanche, Malene Balys, Jonathan Foox, Chistopher E Mason, Robert Steen, Marcy Kuentzel and 3 more

Abstract read
In one paragraph

Article in Journal of biomolecular techniques : JBT, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Long Non-Coding RNA Function in Smooth Muscle Cell Plasticity and Atherosclerosis.Arteriosclerosis, thrombosis, and vascular biology · 2025
    Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Single-cell sequencing: promises and challenges for human genetics.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2022
    Article
  14. Review
  15. Review
  16. Review
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

13 authors.

John M AshtonUniversity of Rochester Medical Center, University of Rochester, West Henrietta, New York 14642, USA.
Hubert RehrauerFunctional Genomics Center Zurich, ETH and University of Zurich, CH-8057 Zurich, Switzerland.
Jason MyersUniversity of Rochester Medical Center, University of Rochester, West Henrietta, New York 14642, USA.
Jacqueline MyersUniversity of Rochester Medical Center, University of Rochester, West Henrietta, New York 14642, USA.
Michelle ZancheUniversity of Rochester Medical Center, University of Rochester, West Henrietta, New York 14642, USA.
Malene BalysUniversity of Rochester Medical Center, University of Rochester, West Henrietta, New York 14642, USA.
Jonathan FooxDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY10065, USA.
Chistopher E MasonDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY10065, USA.
Robert SteenDepartment of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.
Marcy KuentzelEnvironmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, Mississippi 39180, USA.
Catharine AquinoFunctional Genomics Center Zurich, ETH and University of Zurich, CH-8057 Zurich, Switzerland.
Natàlia Garcia-ReyeroEnvironmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, Mississippi 39180, USA.
Sridar V ChitturCenter for Functional Genomics, University at Albany-SUNY, Rensselaer, New York 12144, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) offers great new opportunities for increasing our understanding of complex biological processes. In particular, development of an accurate Human Cell Atlas is largely dependent on the rapidly advancing technologies and molecular chemistries employed in scRNA-seq. These advances have already allowed an increase in throughput for scRNA-seq from 96 to 80,000 cells on a single instrument run by capturing cells within nanoliter droplets. Although this increase in throughput is critical for many experimental questions, a thorough comparison between microfluidic-based, plate-based, and droplet-based technologies or between multiple available platforms utilizing these technologies is largely lacking. Here, we report scRNA-seq data from SUM149PT cells treated with the histone deacetylase inhibitor trichostatin A versus untreated controls across several scRNA-seq platforms (Fluidigm C1, WaferGen iCell8, 10x Genomics Chromium Controller, and Illumina/BioRad ddSEQ). The primary goal of this project was to demonstrate RNA sequencing methods for profiling the ultra-low amounts of RNA present in individual cells, and this report discusses the results of the study, as well as technical challenges and lessons learned and present general guidelines for best practices in sample preparation and analysis.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisHigh-Throughput Nucleotide SequencingHumansRNASequence Analysis, RNARNAplatformsRNA-seqsingle cell

Identifiers

PMID35837267
PMCPMC9258609

What OpenQuestion holds

Textmetadata
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.