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

Authors :
González-Solares, Eduardo A.
Dariush, Ali
González-Fernández, Carlos
Yoldaş, Aybüke Küpcü
Molaeinezhad, Alireza
Al Sa’d, Mohammad
Smith, Leigh
Whitmarsh, Tristan
Millar, Neil
Chornay, Nicholas
Falciatori, Ilaria
Fatemi, Atefeh
Goodwin, Daniel
Kuett, Laura
Mulvey, Claire M.
Ribes, Marta Páez
Qosaj, Fatime
Roth, Andrew
Vázquez-García, Ignacio
Watson, Spencer S.
Source :
Biological Imaging; 2023, Vol. 3, p1-32, 32p
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
Volume :
3
Database :
Complementary Index
Journal :
Biological Imaging
Publication Type :
Academic Journal
Accession number :
176459239
Full Text :
https://doi.org/10.1017/S2633903X23000090