AbstractHigh-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software programs for image analysis workflows typically do not allow full customization and adoption of new image processing algorithms in the analysis modules.

摘要高通量成像（HTI）从大量实验扰动中产生复杂的成像数据集。用于图像分析工作流的商业HTI软件程序通常不允许在分析模块中完全定制和采用新的图像处理算法。

While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities.

虽然开源HTI分析平台在工作流程中提供了单个模块，例如核分割，斑点检测或细胞跟踪，但它们通常在集成新颖的分析模块或算法方面受到限制。在这里，我们介绍高通量图像处理软件（HiTIPS），以扩大现有HTI分析功能的范围和定制。

HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, nucleus registration, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new analysis modules for existing analysis pipelines and to adding new analysis modules.

HiTIPS结合了先进的图像处理和机器学习算法，用于自动细胞和细胞核分割，斑点信号检测，细胞核跟踪，细胞核配准，斑点跟踪和斑点信号强度量化。此外，HiTIPS还提供了一个图形用户界面，可以为现有分析管道集成新的分析模块，也可以添加新的分析模块。

To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI software platform for a variety of cell biology applications..

为了证明HiTIPS的实用性，我们提供了高通量DNA FISH，免疫荧光（IF）和单细胞转录活细胞成像的图像分析工作流程的三个示例。总而言之，我们证明了HiTIPS是一种用户友好，灵活且开源的HTI软件平台，可用于各种细胞生物学应用。。

IntroductionHigh-Throughput Imaging (HTI) fully automates the acquisition and analysis of large fluorescence microscopy imaging datasets. HTI was originally developed to provide phenotypic readouts for large high-throughput chemical screens to identify compounds with desirable therapeutic activities1,2.

简介高通量成像（HTI）完全自动化了大型荧光显微镜成像数据集的采集和分析。HTI最初是为了为大型高通量化学筛选提供表型读数，以鉴定具有理想治疗活性的化合物1,2。

Since then, this technology has also been widely adopted to work in conjunction with functional genomics screens to identify molecular pathways involved in a variety of cellular functions. Furthermore, HTI has been extensively implemented in more traditional cell biology applications, where the automation of image acquisition and analysis has been used to systematically quantify at the single-cell level phenotypes that are heterogeneous, rare, or dynamic in cellular populations2.The study of nuclear architecture and gene expression has particularly benefited from HTI.

从那时起，这项技术也被广泛采用，与功能基因组学筛选相结合，以鉴定涉及多种细胞功能的分子途径。此外，HTI已被广泛应用于更传统的细胞生物学应用中，其中图像采集和分析的自动化已被用于系统地量化细胞群体中异质，罕见或动态的单细胞水平表型2。核结构和基因表达的研究特别受益于HTI。

DNA Fluorescence In Situ Hybridization (FISH)-based HTI imaging has been used to study the spatial organization of genes and chromosomes within the nucleus, providing insights into the mechanisms of gene regulation and nuclear architecture. For example, FISH-based HTI has been used to study the three-dimensional organization of the genome3,4,5,6,7.

基于DNA荧光原位杂交（FISH）的HTI成像已被用于研究细胞核内基因和染色体的空间组织，为基因调控和核结构的机制提供了见识。例如，基于FISH的HTI已被用于研究基因组3,4,5,6,7的三维组织。

In addition, immunofluorescence (IF)-based HTI assays have helped probe nuclear architecture using fluorescently labeled endogenous architectural markers in combination with functional genomics screens8,9,10,11,12,13. Finally, HTI has also been used to explore the dynamics of transcription initiation and RNA splicing in live cells and at the single-cell level14,15.HTI has been enabled by the development of automated microscopy platforms and image analysis software to rapidly acquire and process large amounts of fluorescence microscopy data.

此外，基于免疫荧光（IF）的HTI分析有助于使用荧光标记的内源性结构标记结合功能基因组学筛选来探测核结构8,9,10,11,12,13。最后，HTI还被用于探索活细胞和单细胞水平的转录起始和RNA剪接的动力学14,15。HTI已经通过开发自动显微镜平台和图像分析软件来快速获取和处理大量荧光显微镜数据。

These tools allow the .

这些工具允许。

Data availability

数据可用性

The original imaging metadata generated by our high-throughput microscopes follow most of the QUAREP-LIMI guidelines64,65 and includes all the microscope and imaging settings used to acquire the data. In addition, we have also generated a additional set of image acquisition metadata in the QUAREP-LIMI json format using the Micro-Meta App66.

我们的高通量显微镜生成的原始成像元数据遵循大多数QUAREP-LIMI指南64,65，并包括用于获取数据的所有显微镜和成像设置。此外，我们还使用Micro Meta App66以QUAREP-LIMI json格式生成了另外一组图像采集元数据。

All the images and the image acquisition metadata used in the manuscript have been deposited at BioImage Archive67 under accession number S-BIAD1043 at: https://www.ebi.ac.uk/biostudies/BioImages/studies/S-BIAD1043..

手稿中使用的所有图像和图像采集元数据均已保存在BioImage Archive67中，登录号为S-BIAD1043，网址为：https://www.ebi.ac.uk/biostudies/BioImages/studies/S-BIAD1043..

Code availability

代码可用性

The HiTIPS code base can be found at https://github.com/CBIIT/HiTIPS. A complete guide describing the HiTIPS package structure and its embedded functions, installation and user instruction, results tables description, and developers guide to add new analysis methods is available at https://hitips.readthedocs.io/en/latest/..

HiTIPS代码库可以在https://github.com/CBIIT/HiTIPS.有关HiTIPS软件包结构及其嵌入式功能、安装和用户说明、结果表说明以及添加新分析方法的开发人员指南的完整指南，请访问https://hitips.readthedocs.io/en/latest/..

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Download referencesAcknowledgementsWe would like to thank all the members of the Misteli and Larson laboratories for insightful discussions on high-throughput imaging and automated image analysis. This work utilized the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov).

下载参考文献致谢我们要感谢Misteli和Larson实验室的所有成员就高通量成像和自动图像分析进行了深入的讨论。这项工作利用了NIH HPC Biowulf集群的计算资源(http://hpc.nih.gov)。

We would like to thank the NIH HPC group for their help with data management and software package management. Finally, we would also like to thank the anonymous reviewers for their constructive criticism and feedback for our work, which have substantially improved the original version of the manuscript.

我们要感谢NIH HPC小组在数据管理和软件包管理方面的帮助。最后，我们还要感谢匿名审稿人对我们的工作提出的建设性批评和反馈，这些批评和反馈大大改进了手稿的原始版本。

Research in the Misteli Lab, Larson Lab, and HiTIF was supported by the Intramural Research Program of the NIH, NCI, Center for Cancer Research via 1-ZIA-BC010309-24, 1-ZIA-BC011383-12, and 1-ZIC-BC011567-09, respectively.FundingOpen access funding provided by the National Institutes of Health.Author informationAuthor notesThese authors contributed equally: Faisal Almansour, Krishnendu Guin and Varun Sood.Authors and AffiliationsHigh-Throughput Imaging Facility, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USAAdib Keikhosravi & Gianluca PegoraroCell Biology of Genomes, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USAFaisal Almansour, Krishnendu Guin, Varun Sood & Tom MisteliSystem Biology of Gene Expression, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USAChristopher H.

Misteli实验室，Larson实验室和HiTIF的研究得到了NIH，NCI，癌症研究中心的壁内研究计划的支持，分别通过1-ZIA-BC010309-24、1-ZIA-BC011383-12和1-ZIC-BC011567-09。基金由国立卫生研究院提供的开放获取资金。作者信息作者注意到，这些作者做出了同样的贡献：费萨尔·阿尔曼苏尔，克里斯南多·奎恩和瓦伦·索德。作者和附属机构国家癌症研究所，国家卫生研究所，贝塞斯达，马里兰州，20892，USADIB Keikhosravi＆Gianluca PegoraroCell基因组生物学，国家癌症研究所，国家卫生研究所，贝塞斯达，马里兰州，20892，USAFaisal Almansour，Krishnendu Guin，Varun Sood＆Tom MisteliSystem基因表达生物学，国家癌症研究所，国家卫生研究所，贝塞斯达，马里兰州，20892，USAChristoper H。

Bohrer, Nadezda A. Fursova, Varun Sood & Daniel R. LarsonDepartment of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical School, Washington, DC, 20057, USAFaisal AlmansourAuthorsAdib KeikhosraviView author publicationsYou can also search for this author in.

Bohrer，Nadezda A.Fursova，Varun Sood＆Daniel R.LarsonDepartment of Biochemistry and Molecular and Cellular Biology，Georgetown University Medical School，Washington，DC，20057，USAFaisal AlmansourAuthorsAdib KeikhosraviView author Publications您也可以在中搜索这位作者。

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PubMed Google ScholarContributionsA.K. and G.P. established the requirements for HiTIPS. A.K. wrote all the HiTIPS code base. F.A., K.G., and V.S. performed cell culture and treated cells for DNA FISH, IF, and live cell imaging, respectively. F.A., K.G., and V.S. acquired the images with high-throughput microscopes.

PubMed谷歌学术贡献。K、 和G.P.制定了HiTIPS的要求。A、 K.编写了所有HiTIPS代码库。F、 。F、 A.，K.G。和V.S.用高通量显微镜获取了这些图像。

A.K., F.A., and K.G. analyzed the high-throughput imaging datasets using HiTIPS and performed statistical analysis and plotting. A.K., F.A., K.G., V.S., N.F., C.H.B., D.R.L., and T.M., and G.P. provided guidance and feedback on the algorithms for image analysis and on the design of the graphical user interface.

A、 K.，F.A。和K.G.使用HiTIPS分析了高通量成像数据集，并进行了统计分析和绘图。A、 K.，F.A.，K.G.，V.S.，N.F.，C.H.B.，D.R.L.，和T.M.，以及G.P.提供了关于图像分析算法和图形用户界面设计的指导和反馈。

A.K. and G.P. wrote the manuscript. All authors edited and approved the manuscript.Corresponding authorCorrespondence to.

A、 K.和G.P.写了手稿。所有作者都编辑并批准了手稿。对应作者对应。

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Reprints and permissionsAbout this articleCite this articleKeikhosravi, A., Almansour, F., Bohrer, C.H. et al. High-throughput image processing software for the study of nuclear architecture and gene expression.

转载和许可本文引用本文Keikhosravi，A.，Almansour，F.，Bohrer，C.H。等人。用于研究核结构和基因表达的高通量图像处理软件。

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着丝粒染色质结构高通量筛选图像处理表型筛选软件翻译

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