Evidence map›Paper›PMID 30728144›Full record

ReviewBlood2019

New insights into hematopoietic differentiation landscapes from single-cell RNA sequencing.

Sam Watcham, Iwo Kucinski, Berthold Gottgens

Open access · bronzeAbstract readReview
In one paragraph

Review in Blood, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
4.5field-weighted citation impact, top 4% of its field
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

56 citing papers in PubMed, 86 citations in OpenAlex.

  1. Article
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  12. Immunological face of megakaryocytes.Frontiers of medicine · 2024
    Review
  13. Article
  14. Article
  15. Heterogeneity of platelets and their responses.Research and practice in thrombosis and haemostasis · 2024
    Article
  16. Article
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  18. Review
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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

3 authors at 1 institution in 1 country.

Sam WatchamDepartment of Haematology and Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-8399-7875
Iwo KucinskiDepartment of Haematology and Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-9385-0359
Berthold GottgensDepartment of Haematology and Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-6302-5705
Wellcome/MRC Cambridge Stem Cell Institute · GB

Funding

VISION: ValIdated Systematic IntegratiON of epigenomic dataR24DK106766 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2016 to 2020
$6.2M
Cancer Research UK 21762Medical Research Council MC_PC_12009Medical Research Council MR/M008975/1Medical Research Council MR/S036113/1NIDDK NIH HHS R24 DK106766Wellcome Trust
6 · The paper itself

Abstract

Single-cell transcriptomics has recently emerged as a powerful tool to analyze cellular heterogeneity, discover new cell types, and infer putative differentiation routes. The technique has been rapidly embraced by the hematopoiesis research community, and like other technologies before, single-cell molecular profiling is widely expected to make important contributions to our understanding of the hematopoietic hierarchy. Much of this new interpretation relies on inference of the transcriptomic landscape as a representation of existing cellular states and associated transitions among them. Here we review how this model allows, under certain assumptions, charting of time-resolved differentiation trajectories with unparalleled resolution and how the landscape of multipotent cells may be rather devoid of discrete structures, challenging our preconceptions about stem and progenitor cell types and their organization. Finally, we highlight how promising technological advances may convert static differentiation landscapes into a dynamic cell flux model and thus provide a more holistic understanding of normal hematopoiesis and blood disorders.

Indexed as

HematopoiesisAnimalsHematopoietic Stem CellsHumansSequence Analysis, RNASingle-Cell Analysis

Identifiers

PMID30728144
PMCPMC6440294
OpenAlexW2912490305

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.