SCP Viz - A universal graphical user interface for single protein analysis in single cell proteomics datasets.
SCP Viz - A universal graphical user interface for single protein analysis in single cell proteomics datasets.
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SCP Viz - 用于单细胞蛋白质组数据集中的单一蛋白质分析的通用图形用户界面。
DOI：
10.1101/2023.08.29.555397
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Orsburn,BenjaminC
中科院分区：
文献类型：
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作者：
Warshanna,Ahmed;Orsburn,BenjaminC
单细胞蛋白质组学（SCP）需要分析数十到数千个单个人类细胞来得出生物学结论。然而，在输出数据中评估单个蛋白质的丰度提出了相当大的挑战，并且目前不存在简单的通用解决方案。为了解决这个问题，我们开发了SCP Viz，这是一个具有图形用户界面的统计软件包，可以处理任何仪器或数据处理软件的小型和大型SCP输出。在该软件中，可以以各种方式绘制单个蛋白质的丰度，使用未经调整或归一化的输出。这些输出也可以在软件中进行转换或估算。SCP Viz提供了多种绘图选项，可以帮助识别组间显著改变的蛋白质，无论是在定量转化之前还是之后。在发现单个细胞的亚群后，用户可以使用简单的基于文本的过滤器轻松地重新组合感兴趣的细胞。当以这种方式使用时，SCP Viz允许用户在单个蛋白质，细胞或已识别的亚细胞群体的水平上可视化蛋白质组异质性。SCP Viz与MaxQuant、FragPipe、SpectroNaut和Proteome Discoverer的输出文件兼容，并且应该与其他格式一样好用。SCP Viz可在https://github.com/orsburn/SCPViz上公开获取。对于演示，用户可以从GitHub下载我们的测试数据，并在https://orsburnlab.shinyapps.io/SCPViz/上使用接受用户输入进行分析的在线版本。
Single cell proteomics (SCP) requires the analysis of dozens to thousands of single human cells to draw biological conclusions. However, assessing of the abundance of single proteins in output data presents a considerable challenge, and no simple universal solutions currently exist. To address this, we developed SCP Viz, a statistical package with a graphical user interface that can handle small and large scale SCP output from any instrument or data processing software. In this software, the abundance of individual proteins can be plotted in a variety of ways, using either unadjusted or normalized outputs. These outputs can also be transformed or imputed within the software. SCP Viz offers a variety of plotting options which can help identify significantly altered proteins between groups, both before and after quantitative transformations. Upon the discovery of subpopulations of single cells, users can easily regroup the cells of interest using straightforward text-based filters. When used in this way, SCP Viz allows users to visualize proteomic heterogeneity at the level of individual proteins, cells, or identified subcellular populations. SCP Viz is compatible with output files from MaxQuant, FragPipe, SpectroNaut, and Proteome Discoverer, and should work equally well with other formats. SCP Viz is publicly available at https://github.com/orsburn/SCPViz. For demonstrations, users can download our test data from GitHub and use an online version that accepts user input for analysis at https://orsburnlab.shinyapps.io/SCPViz/.