Research Group Bioinformatics, Fraunhofer ITEM, Hannover, Germany.
Institute of Computer Science, Department of Mathematics and Computer Science, Goethe University, Frankfurt, Germany.
BMC Bioinformatics. 2023 Apr 17;24(1):150. doi: 10.1186/s12859-023-05266-4.
Gene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to to changes of the underlying technologies data sets from different technologies are often difficult to compare and thus a multitude of already available data becomes difficult to use. We present a web application that abstracts away mathematical and programmatical details in order to enable a convenient and customizable analysis of microarray data for large-scale reproducibility studies. In addition, the web application provides a feature that allows easy access to large microarray repositories.
Our web application consists of three basic steps which are necessary for a differential gene expression analysis as well as Gene Ontology (GO) enrichment analysis and the comparison of multiple analysis results. Genealyzer can handle Affymetrix data as well as one-channel and two-channel Agilent data. All steps are visualized with meaningful plots. The application offers flexible analysis while being intuitively operable.
Our web application provides a unified platform for analysing microarray data, while allowing users to compare the results of different technologies and organisms. Beyond reproducibility, this also offers many possibilities for gaining further insights from existing study data, especially since data from different technologies or organisms can also be compared. The web application can be accessed via this URL: https://genealyzer.item.fraunhofer.de/ . Login credentials can be found at the end.
基因表达谱分析是药物开发或功能基因分析等领域广泛采用的方法。基因表达实验的微阵列数据仍然常用于回顾性分析，并且广泛可用。然而，由于底层技术的变化，来自不同技术的数据通常难以比较，因此大量已经可用的数据变得难以使用。我们提出了一个 Web 应用程序，它抽象了数学和程序细节，以便能够方便地对大规模可重复性研究中的微阵列数据进行可定制的分析。此外，该 Web 应用程序还提供了一个功能，可轻松访问大型微阵列存储库。
我们的 Web 应用程序由三个基本步骤组成，这些步骤是差异基因表达分析以及基因本体论（GO）富集分析和多个分析结果比较所必需的。Genealyzer 可以处理 Affymetrix 数据以及单通道和双通道 Agilent 数据。所有步骤都用有意义的图进行可视化。该应用程序提供了灵活的分析，同时具有直观的操作性。
我们的 Web 应用程序为分析微阵列数据提供了一个统一的平台，同时允许用户比较不同技术和生物体的结果。除了可重复性之外，这还为从现有研究数据中获得更多见解提供了许多可能性，特别是因为还可以比较来自不同技术或生物体的数据。该 Web 应用程序可通过以下 URL 访问：https://genealyzer.item.fraunhofer.de/ 。登录凭据可在末尾找到。
