Evidence map›Paper›PMID 30890159›Full record

ArticleGenome biology2019

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells.

F Alexander Wolf, Fiona K Hamey, Mireya Plass, Jordi Solana, Joakim S Dahlin, Berthold Göttgens, Nikolaus Rajewsky, Lukas Simon, Fabian J Theis

Abstract read
In one paragraph

Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,058 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,058citing 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

1,058 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Spatiotemporally primed coelomic epithelium and supporting-like cells establish the dual origin of granulosa cells.Proceedings of the National Academy of Sciences of the United States of America · 2026
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998 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

9 authors.

F Alexander WolfHelmholtz Center Munich - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany.ORCID 0000-0002-8760-7838
Fiona K HameyDepartment of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
Mireya PlassBerlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany.
Jordi SolanaBerlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany.
Joakim S DahlinDepartment of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
Berthold GöttgensDepartment of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
Nikolaus RajewskyBerlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany.
Lukas SimonHelmholtz Center Munich - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany.
Fabian J TheisHelmholtz Center Munich - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany. fabian.theis@helmholtz-muenchen.de.

Funding

Cancer Research UKMedical Research Council MC_PC_12009Wellcome Trust 206328/Z/17/Z
6 · The paper itself

Abstract

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions ( https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.

Indexed as

Computer GraphicsGene Expression Regulation, DevelopmentalAlgorithmsAnimalsComputational BiologyEmbryo, NonmammalianHematopoietic Stem CellsHigh-Throughput Nucleotide SequencingHumansPlanariansReference StandardsSequence Analysis, RNASingle-Cell AnalysisSoftwareZebrafish

Identifiers

PMID30890159
PMCPMC6425583

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Registered trials

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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.