Kai O. Kreissner, Benjamin Faller, Ivan Talucci, Hans M. Maric
{"title":"MARTin—an open-source platform for microarray analysis","authors":"Kai O. Kreissner, Benjamin Faller, Ivan Talucci, Hans M. Maric","doi":"10.3389/fbinf.2024.1329062","DOIUrl":null,"url":null,"abstract":"Background: Microarray technology has brought significant advancements to high-throughput analysis, particularly in the comprehensive study of biomolecular interactions involving proteins, peptides, and antibodies, as well as in the fields of gene expression and genotyping. With the ever-increasing volume and intricacy of microarray data, an accurate, reliable and reproducible analysis is essential. Furthermore, there is a high level of variation in the format of microarrays. This not only holds true between different sample types but is also due to differences in the hardware used during the production of the arrays, as well as the personal preferences of the individual users. Therefore, there is a need for transparent, broadly applicable and user-friendly image quantification techniques to extract meaningful information from these complex datasets, while also addressing the challenges posed by specific microarray and imager formats, which can flaw analysis and interpretation.Results: Here we introduce MicroArray Rastering Tool (MARTin), as a versatile tool developed primarily for the analysis of protein and peptide microarrays. Our software provides state-of-the-art methodologies, offering researchers a comprehensive tool for microarray image quantification. MARTin is independent of the microarray platform used and supports various configurations including high-density formats and printed arrays with significant x and y offsets. This is made possible by granting the user the ability to freely customize parts of the application to their specific microarray format. Thanks to built-in features like adaptive filtering and autofit, measurements can be done very efficiently and are highly reproducible. Furthermore, our tool integrates metadata management and integrity check features, providing a straightforward quality control method, along with a ready-to-use interface for in-depth data analysis. This not only promotes good scientific practice in the field of microarray analysis but also enhances the ability to explore and examine the generated data.Conclusion: MARTin has been developed to empower its users with a reliable, efficient, and intuitive tool for peptidomic and proteomic array analysis, thereby facilitating data-driven discovery across disciplines. Our software is an open-source project freely available via the GNU Affero General Public License licence on GitHub.","PeriodicalId":507586,"journal":{"name":"Frontiers in Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fbinf.2024.1329062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Microarray technology has brought significant advancements to high-throughput analysis, particularly in the comprehensive study of biomolecular interactions involving proteins, peptides, and antibodies, as well as in the fields of gene expression and genotyping. With the ever-increasing volume and intricacy of microarray data, an accurate, reliable and reproducible analysis is essential. Furthermore, there is a high level of variation in the format of microarrays. This not only holds true between different sample types but is also due to differences in the hardware used during the production of the arrays, as well as the personal preferences of the individual users. Therefore, there is a need for transparent, broadly applicable and user-friendly image quantification techniques to extract meaningful information from these complex datasets, while also addressing the challenges posed by specific microarray and imager formats, which can flaw analysis and interpretation.Results: Here we introduce MicroArray Rastering Tool (MARTin), as a versatile tool developed primarily for the analysis of protein and peptide microarrays. Our software provides state-of-the-art methodologies, offering researchers a comprehensive tool for microarray image quantification. MARTin is independent of the microarray platform used and supports various configurations including high-density formats and printed arrays with significant x and y offsets. This is made possible by granting the user the ability to freely customize parts of the application to their specific microarray format. Thanks to built-in features like adaptive filtering and autofit, measurements can be done very efficiently and are highly reproducible. Furthermore, our tool integrates metadata management and integrity check features, providing a straightforward quality control method, along with a ready-to-use interface for in-depth data analysis. This not only promotes good scientific practice in the field of microarray analysis but also enhances the ability to explore and examine the generated data.Conclusion: MARTin has been developed to empower its users with a reliable, efficient, and intuitive tool for peptidomic and proteomic array analysis, thereby facilitating data-driven discovery across disciplines. Our software is an open-source project freely available via the GNU Affero General Public License licence on GitHub.
背景:微阵列技术为高通量分析带来了重大进步,尤其是在涉及蛋白质、肽和抗体的生物分子相互作用的综合研究以及基因表达和基因分型领域。随着微阵列数据的数量和复杂性不断增加,准确、可靠和可重复的分析至关重要。此外,微阵列的格式差异很大。这不仅是不同样本类型之间的差异,也是由于芯片生产过程中使用的硬件不同以及用户的个人偏好造成的。因此,我们需要透明、广泛适用且用户友好的图像量化技术,以便从这些复杂的数据集中提取有意义的信息,同时解决特定微阵列和成像仪格式带来的挑战,这些挑战可能会影响分析和解释:我们在此介绍微阵列栅格化工具(MARTin),它是一种多功能工具,主要用于分析蛋白质和肽微阵列。我们的软件提供了最先进的方法,为研究人员提供了微阵列图像量化的综合工具。MARTin 与所使用的微阵列平台无关,支持各种配置,包括高密度格式和具有显著 x 和 y 偏移的印刷阵列。用户可以根据自己特定的微阵列格式自由定制应用程序的各个部分,从而使上述功能成为可能。得益于自适应滤波和自动拟合等内置功能,测量工作可以非常高效地完成,并具有很高的可重复性。此外,我们的工具还集成了元数据管理和完整性检查功能,提供了一种直接的质量控制方法,以及一个用于深入数据分析的即用型界面。这不仅促进了微阵列分析领域的良好科学实践,还增强了探索和检查生成数据的能力:开发 MARTin 的目的是为用户提供可靠、高效、直观的肽组和蛋白质组阵列分析工具,从而促进跨学科的数据驱动发现。我们的软件是一个开源项目,可通过 GitHub 上的 GNU Affero 通用公共许可证免费获取。