Evidence map›Paper›PMID 31308548›Full record

ArticleNature methods2019

Joint analysis of heterogeneous single-cell RNA-seq dataset collections.

Nikolas Barkas, Viktor Petukhov, Daria Nikolaeva, Yaroslav Lozinsky, Samuel Demharter, Konstantin Khodosevich, Peter V Kharchenko

Abstract read
In one paragraph

Article in Nature methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
184citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

124 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

7 authors.

Nikolas BarkasDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4675-0718
Viktor PetukhovDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Daria NikolaevaDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Yaroslav LozinskyDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Samuel DemharterBiotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Konstantin KhodosevichBiotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Peter V KharchenkoDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. peter_kharchenko@hms.harvard.edu.ORCID http://orcid.org/0000-0002-6036-5875

Funding

Statistical methods for analysis of single-cell variabilityR01HL131768 · NHLBI · HARVARD MEDICAL SCHOOL · PI KHARCHENKO, PETER V · 2015 to 2019
$2.4M
NHLBI NIH HHS R01 HL131768
6 · The paper itself

Abstract

Single-cell RNA sequencing is often applied in study designs that include multiple individuals, conditions or tissues. To identify recurrent cell subpopulations in such heterogeneous collections, we developed Conos, an approach that relies on multiple plausible inter-sample mappings to construct a global graph connecting all measured cells. The graph enables identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.

Indexed as

Databases, GeneticGene Expression ProfilingBone MarrowComputational BiologyHigh-Throughput Nucleotide SequencingHumansSingle-Cell Analysis

Identifiers

PMID31308548
PMCPMC6684315

What OpenQuestion holds

Textmetadata
LicenceTDM
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.