Institute of Computer Science, University of Tartu, Narva mnt 18, Tartu, 51009, Estonia.
Quretec Ltd, Ülikooli 6a, Tartu, 51003, Estonia.
BMC Bioinformatics. 2020 Sep 17;21(1):411. doi: 10.1186/s12859-020-03722-z.
Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge.
Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows.
PAWER is freely available at https://biit.cs.ut.ee/pawer .
蛋白质微阵列是一种成熟的方法，可以并行地描述数千种蛋白质的活性水平。分析蛋白质微阵列数据是复杂且耗时的，而现有的解决方案要么已经过时，要么没有编程技能就难以使用。典型的数据分析流程包括数据预处理步骤，然后是差异表达分析，再通过功能富集将其置于上下文中。通常，生物学家需要通过组合一组不相关的工具来分析实验数据来组装自己的工作流程。假设这些工具大多是由不同的生物信息学小组独立开发的，因此让它们协同工作可能是一个真正的挑战。
我们在这里介绍 PAWER，这是一款专门用于蛋白质微阵列分析的在线网络工具。PAWER 使生物学家能够一次性完成所有必要的分析步骤。PAWER 通过用户友好的界面提供了最先进的计算方法，从而生成可发表的插图。我们还提供了一个 R 包，用于更高级的用例，例如定制的分析工作流程。
PAWER 可在 https://biit.cs.ut.ee/pawer 免费获得。
