Machlab Daniel A, Velez Gabriel, Bassuk Alexander G, Mahajan Vinit B
1Omics Laboratory, Stanford University, Palo Alto, CA USA.
2Department of Ophthalmology, Byers Eye Institute, Stanford University, 1651 Page Mill Road, Palo Alto, CA 94304 USA.
Source Code Biol Med. 2018 Nov 12;13:3. doi: 10.1186/s13029-018-0070-0. eCollection 2018.
In proteomics studies, liquid chromatography tandem mass spectrometry data (LC-MS/MS) is quantified by spectral counts or by some measure of ion abundance. Downstream comparative analysis of protein content (e.g. Venn diagrams and network analysis) typically does not include this quantitative data and critical information is often lost. To avoid loss of spectral count data in comparative proteomic analyses, it is critical to implement a tool that can rapidly retrieve this information.
We developed ProSave, a free and user-friendly Java-based program that retrieves spectral count data from a curated list of proteins in a large proteomics dataset. ProSave allows for the management of LC-MS/MS datasets and rapidly retrieves spectral count information for a desired list of proteins.
ProSave is open source and freely available at https://github.com/MahajanLab/ProSave. The user manual, implementation notes, and description of methodology and examples are available on the site.
在蛋白质组学研究中,液相色谱串联质谱数据(LC-MS/MS)通过谱图计数或某种离子丰度测量方法进行定量。蛋白质含量的下游比较分析(例如维恩图和网络分析)通常不包括此定量数据,关键信息常常丢失。为避免在比较蛋白质组分析中丢失谱图计数数据,实施一个能够快速检索此信息的工具至关重要。
我们开发了ProSave,这是一个基于Java的免费且用户友好的程序,可从大型蛋白质组学数据集中经过整理的蛋白质列表中检索谱图计数数据。ProSave允许管理LC-MS/MS数据集,并能快速检索所需蛋白质列表的谱图计数信息。
ProSave是开源的,可在https://github.com/MahajanLab/ProSave上免费获取。该网站提供用户手册、实施说明以及方法描述和示例。