Evidence map›Paper›PMID 38487685›Full record

ArticleBiological imaging2023

Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure.

Eduardo A González-Solares, Ali Dariush, Carlos González-Fernández, Aybüke Küpcü Yoldaş, Alireza Molaeinezhad, Mohammad Al Sa'd, Leigh Smith, Tristan Whitmarsh, Neil Millar, Nicholas Chornay and 22 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biological imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. The dawn of spatial omics.Science (New York, N.Y.) · 2023
    Review
  4. 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

32 authors at 7 institutions in 4 countries.

Eduardo A González-SolaresInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Ali DariushInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Carlos González-FernándezInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Aybüke Küpcü YoldaşInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Alireza MolaeinezhadInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Mohammad Al Sa'dInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Leigh SmithInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Tristan WhitmarshInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Neil MillarInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Nicholas ChornayInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
Ilaria FalciatoriCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Atefeh FatemiCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Daniel GoodwinMcGovern Institute, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Laura KuettDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Claire M MulveyCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Marta Páez RibesCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Fatime QosajCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Andrew RothDepartment of Computer Science, University of British Columbia, Vancouver, BC, Canada.
Ignacio Vázquez-GarcíaHerbert and Florence Irving Institute for Cancer Dynamics, Columbia University, New York, NY, USA.
Spencer S WatsonDepartment of Oncology and Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland.
Jonas WindhagerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0002-2111-5291
Samuel AparicioDepartment of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Bernd BodenmillerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Ed BoydenMcGovern Institute, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Carlos CaldasCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Owen HarrisSúil Interactive, Dublin, Ireland.
Sohrab P ShahDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Simon TavaréCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
CRUK IMAXT Grand Challenge Team
Dario BressanCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Gregory J HannonCRUK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, United Kingdom.
Nicholas A WaltonInstitute of Astronomy, University of Cambridge, Cambridge, United Kingdom.
University of Cambridge · GBUniversity of Zurich · CHMemorial Sloan Kettering Cancer Center · USUniversity of British Columbia · CAHoward Hughes Medical Institute · USLudwig Cancer Research · CHMcGovern Institute for Brain Research · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748Wellcome Trust 110161/Z/15/Z
6 · The paper itself

Abstract

With the aim of producing a 3D representation of tumors, imaging and molecular annotation of xenografts and tumors (IMAXT) uses a large variety of modalities in order to acquire tumor samples and produce a map of every cell in the tumor and its host environment. With the large volume and variety of data produced in the project, we developed automatic data workflows and analysis pipelines. We introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located, instead of bringing data to their local computers. Here, we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumor models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT. The automatic pipelines are highly optimized and allow to obtain processed datasets several times quicker than current solutions narrowing the gap between data acquisition and scientific exploitation.

Indexed as

Data managementdata processing and analysisfluorescence microscopyimaging mass cytometry

Identifiers

PMID38487685
PMCPMC10936408
OpenAlexW4365514466

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.