Cited by 1,125Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesMolecular Biology Techniques and Applications

CEL-seq2: sensitive highly-multiplexed single-cell RNA-Seq

Open access
Hashimshony, Tamar, Senderovich, Naftalie, Avital, Gal, Klochendler, Agnes, de Leeuw, Yaron, Anavy, Leon, Gennert, Dave, Li, Shuqiang +5 more·2016·Genome Biology

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13059-016-0938-8

Cites

66 of 66 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • scRNA-seq conducted in the small volumes of the Fluidigm C1 platform outperforms CEL-seq2, Smart-seq, or other commercially available kits in microliter volumes.

    “For example, it has previously been shown that scRNA-seq conducted in the small volumes available in the automated microfluidic platform from Fluidigm (C1 platform) outperforms CEL-seq2, Smart-seq, or other commercially available kits in microliter volumes (Hashimshony et al., 2016; Wu et al., 2014).”

    From Comparative Analysis of Single-Cell RNA Sequencing Methods (2017) · cites this paper as Hashimshony et al., 2016

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Hashimshony, T., Senderovich, N., Avital, G., Klochendler, A., de Leeuw, Y., Anavy, L., Gennert, D., Li, S., Livak, K. J., Rozenblatt-Rosen, O., Dor, Y., Regev, A., & Yanai, I.
Affiliations
  • Technion – Israel Institute of Technology (IL)
  • Hebrew University of Jerusalem (IL)
  • Standard BioTools (United States) (US)
  • Broad Institute (US)
Corresponding author
Yanai, Itai
Venue
Genome Biology
Published
2016-04-28
Volume
17
Issue
1
Pages
77-77
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
OpenAlex
W2342688693
Cited by
1,125
References
66
Citations by year
2026: 59 · 2025: 114 · 2024: 125 · 2023: 111 · 2022: 151 · 2021: 161 · 2020: 129 · 2019: 119 · 2018: 97 · 2017: 44 · 2016: 14 · 2015: 1
FWCI
47.45
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Genome biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Funders
Seventh Framework Programme (310927)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords
single-cell RNA sequencing, single-cell transcriptomics, sequencing sensitivity, cell cycle progression, mouse fibroblasts, cost reduction
MeSH terms
Algorithms, Animals, Cell Cycle, Cells, Cultured, Fibroblasts, Sensitivity and Specificity, Sequence Analysis, RNA, Gene Expression Profiling, Mice, Single-Cell Analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review