Evidence map›Paper›PMID 29850785›Full record

ArticleBioinformatics (Oxford, England)2018

GateFinder: projection-based gating strategy optimization for flow and mass cytometry.

Nima Aghaeepour, Erin F Simonds, David J H F Knapp, Robert V Bruggner, Karen Sachs, Anthony Culos, Pier Federico Gherardini, Nikolay Samusik, Gabriela K Fragiadakis, Sean C Bendall and 6 more

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Making the most of high-dimensional cytometry data.Immunology and cell biology · 2021
    Review
  7. Gut CD4Nature immunology · 2021
    Article
  8. A Cancer Biologist's Primer on Machine Learning Applications in High-Dimensional Cytometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2020
    Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. How Clinical Flow Cytometry Rebooted Sepsis Immunology.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2019
    Review
  15. Article
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

16 authors.

Nima AghaeepourBaxter Laboratory in Stem Cell Biology.
Erin F SimondsDepartment of Neurology, University of California, San Francisco, CA, USA.
David J H F KnappTerry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, BC, Canada.
Robert V BruggnerBaxter Laboratory in Stem Cell Biology.
Karen SachsBaxter Laboratory in Stem Cell Biology.
Anthony CulosDepartment of Anesthesiology, Stanford University, Stanford, CA, USA.
Pier Federico GherardiniBaxter Laboratory in Stem Cell Biology.
Nikolay SamusikBaxter Laboratory in Stem Cell Biology.
Gabriela K FragiadakisBaxter Laboratory in Stem Cell Biology.
Sean C BendallBaxter Laboratory in Stem Cell Biology.
Brice GaudilliereBaxter Laboratory in Stem Cell Biology.
Martin S AngstDepartment of Anesthesiology, Stanford University, Stanford, CA, USA.
Connie J EavesTerry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, BC, Canada.
William A WeissDepartment of Neurology, University of California, San Francisco, CA, USA.
Wendy J FantlDepartment of Obstetrics and Gynecology, Stanford University, Stanford, CA, USA.
Garry P NolanBaxter Laboratory in Stem Cell Biology.

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Supplement to Enhance Wellness and Resiliency in the Graduate EnvironmentT32GM007276 · NIGMS · STANFORD UNIVERSITY · PI MORRISON, ASHBY J. · 1985 to 2023
$32.9M
TRIGGERING CELL DEATH IN B CELL LYMPHOMAP01CA034233 · NCI · STANFORD UNIVERSITY · PI FELSHER, DEAN W · 1985 to 2010
$19.5M
TRANS-NETWORK PROJECTSU54CA143907 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI NOLAN, GARRY P · 2009 to 2013
$15.2M
MODELING THE ROLE OF PROGRESSION IN FOLLICULAR LYMPHOMAU54CA149145 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2010 to 2014
$12.1M
Software & Hardware Inference Engines for Automated Determination of Primary CellR01CA130826 · NCI · STANFORD UNIVERSITY · PI NOLAN, GARRY P · 2008 to 2011
$6.7M
Integrating mass cytometric and transcriptomic profiles of solid tumorsR33CA183692 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WEISS, WILLIAM A · 2014 to 2016
$1.2M
CIHR CIHR 321510NCI NIH HHS P01 CA034233NCI NIH HHS R01 CA130826NCI NIH HHS R33 CA183692NCI NIH HHS U54 CA143907NCI NIH HHS U54 CA149145NIAID NIH HHS HHSN272200700038CNIAID NIH HHS U19 AI057229NIGMS NIH HHS T32 GM007276
6 · The paper itself

Abstract

Motivation: High-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging. Results: Here, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology. Availability and implementation: The GateFinder algorithm is implemented as a free and open-source package for BioConductor: https://nalab.stanford.edu/gatefinder. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsFlow CytometrySoftwareBiomarkersBiomarkers

Identifiers

PMID29850785
PMCPMC6247943

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.