CAT PETR:用于磷酸化和表达数据差异分析的图形用户界面。

IF 0.9 4区 数学 Q3 Mathematics Statistical Applications in Genetics and Molecular Biology Pub Date : 2023-08-21 eCollection Date: 2023-01-01 DOI:10.1515/sagmb-2023-0017
Keegan Flanagan, Steven Pelech, Yossef Av-Gay, Khanh Dao Duc
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引用次数: 0

摘要

抗体微阵列数据提供了一种强大的高通量工具,可用于监测细胞对扰动或遗传操作反应的整体变化。然而,虽然收集此类数据的途径越来越多,但由于缺乏特定的计算工具,对它们的分析受到了限制。我们在此介绍 CAT PETR,这是一款用户友好型网络应用程序,用于对通过抗体微阵列收集的表达和磷酸化数据进行差异分析。我们的应用程序通过提供各种数据输入选项和可视化效果,解决了其他基于图形用户界面的工具的局限性。为了说明其在真实数据上的能力,我们展示了 CAT PETR 利用其先进的可视化和统计选项,既复制了以前的发现,又揭示了更多的见解。
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CAT PETR: a graphical user interface for differential analysis of phosphorylation and expression data.

Antibody microarray data provides a powerful and high-throughput tool to monitor global changes in cellular response to perturbation or genetic manipulation. However, while collecting such data has become increasingly accessible, a lack of specific computational tools has made their analysis limited. Here we present CAT PETR, a user friendly web application for the differential analysis of expression and phosphorylation data collected via antibody microarrays. Our application addresses the limitations of other GUI based tools by providing various data input options and visualizations. To illustrate its capabilities on real data, we show that CAT PETR both replicates previous findings, and reveals additional insights, using its advanced visualization and statistical options.

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来源期刊
CiteScore
1.20
自引率
11.10%
发文量
8
审稿时长
6-12 weeks
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
期刊最新文献
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