Evidence map›Paper›PMID 27121950›Full record

ArticleGenome biology2016

CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq.

Tamar Hashimshony, Naftalie Senderovich, Gal Avital, Agnes Klochendler, Yaron de Leeuw, Leon Anavy, Dave Gennert, Shuqiang Li, Kenneth J Livak, Orit Rozenblatt-Rosen and 3 more

Abstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 647 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
647citing 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

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

  1. Single-cell RNA sequencing offers novel perspectives in viral infection research.Frontiers in cellular and infection microbiology · 2026
    Pooled it
  2. Article
  3. Article
  4. Review
  5. Ten years, tens of millions of cells.Nature biotechnology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Single-cell RNA sequencing in stroke and traumatic brain injury: Current achievements, challenges and future perspectives on transcriptomic profiling.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Review
  17. Article
  18. Article
  19. Article
  20. Review

587 more citing papers are in PubMed but not listed here.

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.

Tamar HashimshonyDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Naftalie SenderovichDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Gal AvitalDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Agnes KlochendlerDepartment of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Yaron de LeeuwDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Leon AnavyDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Dave GennertKlarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA.
Shuqiang LiFluidigm Corporation, 7000 Shoreline Court, Suite 100, South San Francisco, CA, 94080, USA.
Kenneth J LivakFluidigm Corporation, 7000 Shoreline Court, Suite 100, South San Francisco, CA, 94080, USA.
Orit Rozenblatt-RosenKlarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA.
Yuval DorDepartment of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Aviv RegevKlarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA.
Itai YanaiDepartment of Biology, Technion - Israel Institute of Technology, Haifa, Israel. yanai@technion.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm's C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2's increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.

Indexed as

AlgorithmsAnimalsCell CycleCells, CulturedFibroblastsGene Expression ProfilingMiceSensitivity and SpecificitySequence Analysis, RNASingle-Cell Analysis

Identifiers

PMID27121950
PMCPMC4848782

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.