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

IF 0.2 2区 文学 0 LITERATURE, BRITISH ISLES CAHIERS ELISABETHAINS Pub Date : 2023-04-14 eCollection Date: 2023-01-01 DOI:10.1017/S2633903X23000090
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, Ilaria Falciatori, Atefeh Fatemi, Daniel Goodwin, Laura Kuett, Claire M Mulvey, Marta Páez Ribes, Fatime Qosaj, Andrew Roth, Ignacio Vázquez-García, Spencer S Watson, Jonas Windhager, Samuel Aparicio, Bernd Bodenmiller, Ed Boyden, Carlos Caldas, Owen Harris, Sohrab P Shah, Simon Tavaré, Dario Bressan, Gregory J Hannon, Nicholas A Walton
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引用次数: 0

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.

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Xenographs 和肿瘤的成像和分子注释(IMAXT):高通量数据和分析基础设施。
为了生成肿瘤的三维图像,异种移植和肿瘤的成像与分子标注(IMAXT)采用了多种方式获取肿瘤样本,并绘制出肿瘤中每个细胞及其宿主环境的地图。由于该项目产生的数据量大、种类多,我们开发了自动数据工作流程和分析管道。我们引入了一种研究方法,即科学家连接到云环境,在数据所在位置附近进行分析,而不是将数据带到本地计算机。在此,我们将介绍数据和分析基础设施,讨论独特的计算挑战,并描述为生成分子注释肿瘤模型而开发和部署的分析链。配准是通过一种新技术来实现的,该技术涉及球形靶标,在 IMAXT 使用的所有成像模式中都能看到这些靶标。自动流水线经过高度优化,获得处理数据集的速度比目前的解决方案快数倍,缩小了数据获取与科学利用之间的差距。
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来源期刊
CAHIERS ELISABETHAINS
CAHIERS ELISABETHAINS LITERATURE, BRITISH ISLES-
CiteScore
0.30
自引率
20.00%
发文量
39
期刊最新文献
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