Evidence map›Paper›PMID 32293253›Full record

ArticleBMC bioinformatics2020

Brick plots: an intuitive platform for visualizing multiparametric immunophenotyped cell clusters.

Samuel E Norton, Julia K H Leman, Tiffany Khong, Andrew Spencer, Barbara Fazekas de St Groth, Helen M McGuire, Roslyn A Kemp

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Making the most of high-dimensional cytometry data.Immunology and cell biology · 2021
    Review
4 · The record

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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.

Samuel E NortonDepartment of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Julia K H LemanDepartment of Microbiology and Immunology, University of Otago, Dunedin, New Zealand.
Tiffany KhongMyeloma Research Group, Australian Centre for Blood Diseases, Alfred Hospital-Monash University, Melbourne, VIC, Australia.
Andrew SpencerMyeloma Research Group, Australian Centre for Blood Diseases, Alfred Hospital-Monash University, Melbourne, VIC, Australia.
Barbara Fazekas de St GrothRamaciotti Facility for Human Systems Biology, The University of Sydney and Centenary Institute, Sydney, Australia.
Helen M McGuireRamaciotti Facility for Human Systems Biology, The University of Sydney and Centenary Institute, Sydney, Australia. helen.mcguire@sydney.edu.au.
Roslyn A KempDepartment of Microbiology and Immunology, University of Otago, Dunedin, New Zealand. roslyn.kemp@otago.ac.nz.ORCID http://orcid.org/0000-0001-9092-1150

Funding

Australasia Leukemia and Lymphoma Group n/aAustralian National Health and Medical Research Council Early Career Fellowship GNT1037298Cancer Research Trust n/aInternational Society for the Advancement of Cytometry (ISAC) Marylou Ingram Scholars n/aLottery Health Research n/aNZSO Roche Translational Research Fellowship n/aUniversity of Otago n/a
6 · The paper itself

Abstract

backgroundThe advent of mass cytometry has dramatically increased the parameter limit for immunological analysis. New approaches to analysing high parameter cytometry data have been developed to ease analysis of these complex datasets. Many of these methods assign cells into population clusters based on protein expression similarity.

resultsHere we introduce an additional method, termed Brick plots, to visualize these cluster phenotypes in a simplified and intuitive manner. The Brick plot method generates a two-dimensional barcode that displays the phenotype of each cluster in relation to the entire dataset. We show that Brick plots can be used to visualize complex mass cytometry data, both from fundamental research and clinical trials, as well as flow cytometry data.

conclusionBrick plots represent a new approach to visualize complex immunological data in an intuitive manner.

Indexed as

Computer GraphicsFlow CytometryHumansImmunophenotypingMass SpectrometryPhenotypeAnalysisCancerClinicalMass cytometryNK cellsT cells

Identifiers

PMID32293253
PMCPMC7158154

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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.