PrIntMap-R: An Online Application for Intraprotein Intensity and Peptide Visualization from Bottom-Up Proteomics.
PrIntMap-R: An Online Application for Intraprotein Intensity and Peptide Visualization from Bottom-Up Proteomics.
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DOI：
10.1021/acs.jproteome.2c00606
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发表时间：
2023-02-03
影响因子：
4.4
通讯作者：
Champion, Matthew M.
中科院分区：
文献类型：
--
作者：
Weaver, Simon D.;DeRosa, Christine M.;Schultz, Sadie R.;Champion, Matthew M.
关键词：
自下而上的蛋白质组学（BUP）产生丰富的数据，但可视化和分析非常耗时，并且通常需要编程技能。许多工具在蛋白质组水平上分析这些数据，但针对单个蛋白质的选择较少。序列覆盖图是常见的，但不成比例的肽强度。基于丰度的序列覆盖度可视化有助于检测蛋白质亚型、结构域、潜在截短位点、肽“热点”和翻译后修饰（PTM）的定位。冗余堆叠序列覆盖率是设计氢氘交换（HDX）实验的重要工具。可视化工具往往缺乏图形和表格输出的处理后的数据，这使结果的发布复杂化。跨氨基酸序列的定量肽丰度是蛋白质组学工具箱中必不可少的和缺失的工具。在这里，我们创建了PrIntMap-R，这是一个在线应用程序，只需要来自数据库搜索的肽文件和FASTA蛋白质序列。PrIntMap-R生成各种图，用于覆盖的定量可视化;特定序列的注释，PTM，以及与计算的倍数变化或几个强度度量重叠的一个或多个样品的比较。我们展示了包括蛋白质磷酸化、糖基化鉴定和HDX实验消化条件优化在内的用例。PrIntMap-R是免费的，开源的，可以在线运行，无需安装，也可以通过从GitHub下载源代码在本地运行。
Bottom-up proteomics (BUP) produces rich data, but visualization and analysis are time-consuming and often require programming skills. Many tools analyze these data at the proteome-level, but fewer options exist for individual proteins. Sequence coverage maps are common, but do not proportion peptide intensity. Abundance-based visualization of sequence coverage facilitates detection of protein isoforms, domains, potential truncation sites, peptide “hot-spots”, and localization of post-translational modifications (PTMs). Redundant stacked-sequence coverage is an important tool in designing hydrogen–deuterium exchange (HDX) experiments. Visualization tools often lack graphical and tabular-export of processed data which complicates publication of results. Quantitative peptide abundance across amino acid sequences is an essential and missing tool in proteomics toolkits. Here we created PrIntMap-R, an online application that only requires peptide files from a database search and FASTA protein sequences. PrIntMap-R produces a variety of plots for quantitative visualization of coverage; annotation of specific sequences, PTM’s, and comparisons of one or many samples overlaid with calculated fold-change or several intensity metrics. We show use-cases including protein phosphorylation, identification of glycosylation, and the optimization of digestion conditions for HDX experiments. PrIntMap-R is freely available, open source, and can run online with no installation, or locally by downloading source code from GitHub.
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影响因子：
48
作者：
Choi M;Carver J;Chiva C;Tzouros M;Huang T;Tsai TH;Pullman B;Bernhardt OM;Hüttenhain R;Teo GC;Perez-Riverol Y;Muntel J;Müller M;Goetze S;Pavlou M;Verschueren E;Wollscheid B;Nesvizhskii AI;Reiter L;Dunkley T;Sabidó E;Bandeira N;Vitek O
通讯作者：
Vitek O
影响因子：
14.9
作者：
Perez-Riverol Y;Bai J;Bandla C;García-Seisdedos D;Hewapathirana S;Kamatchinathan S;Kundu DJ;Prakash A;Frericks-Zipper A;Eisenacher M;Walzer M;Wang S;Brazma A;Vizcaíno JA
通讯作者：
Vizcaíno JA
影响因子：
3.4
作者：
Searle, Brian C.
通讯作者：
Searle, Brian C.
影响因子：
4.8
作者：
Mullahoo, James;Zhang, Terry;Papanastasiou, Malvina
通讯作者：
Papanastasiou, Malvina
影响因子：
3.3
作者：
Mehta S;Easterly CW;Sajulga R;Millikin RJ;Argentini A;Eguinoa I;Martens L;Shortreed MR;Smith LM;McGowan T;Kumar P;Johnson JE;Griffin TJ;Jagtap PD
通讯作者：
Jagtap PD