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

Details

Serval ID
serval:BIB_5B0B31E590CB
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Imaging and Molecular Annotation of Xenographs and Tumours (IMAXT): High throughput data and analysis infrastructure.
Journal
Biological imaging
Author(s)
González-Solares E.A., Dariush A., González-Fernández C., Küpcü Yoldaş A., Molaeinezhad A., Al Sa'd M., Smith L., Whitmarsh T., Millar N., Chornay N., Falciatori I., Fatemi A., Goodwin D., Kuett L., Mulvey C.M., Páez Ribes M., Qosaj F., Roth A., Vázquez-García I., Watson S.S., Windhager J., Aparicio S., Bodenmiller B., Boyden E., Caldas C., Harris O., Shah S.P., Tavaré S., Bressan D., Hannon G.J., Walton N.A.
Working group(s)
CRUK IMAXT Grand Challenge Team
ISSN
2633-903X (Electronic)
ISSN-L
2633-903X
Publication state
Published
Issued date
2023
Peer-reviewed
Oui
Volume
3
Pages
e11
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
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.
Keywords
Data management, data processing and analysis, fluorescence microscopy, imaging mass cytometry
Pubmed
Open Access
Yes
Create date
22/03/2024 11:30
Last modification date
23/03/2024 8:24
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