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PepC:基于谱计数鉴定差异表达蛋白的蛋白质组学软件。

PepC: proteomics software for identifying differentially expressed proteins based on spectral counting.

机构信息

Insilicos LLC, Seattle, WA 98109, USA.

出版信息

Bioinformatics. 2010 Jun 15;26(12):1574-5. doi: 10.1093/bioinformatics/btq171. Epub 2010 Apr 22.

Abstract

UNLABELLED

Identifying biologically significant changes in protein abundance between two conditions is a key issue when analyzing proteomic data. One widely used approach centers on spectral counting, a label-free method that sums all the tandem mass spectra for a protein observed in an analysis. To assess the significance of the results, we recently combined the t-test and G-test, with random permutation analysis, and we validated this approach biochemically. To automate the statistical method, we developed PepC, a software program that balances the trade-off between the number of differentially expressed proteins identified and the false discovery rate. This tool can be applied to a wide range of proteomic datasets, making data analysis rapid, reproducible and easily interpretable by proteomics specialists and non-specialists alike.

AVAILABILITY AND IMPLEMENTATION

The software is implemented in Java. It has been added to the Trans Proteomic Pipeline project's 'Petunia' web interface, but can also be run as a command line program. The source code is GNU Lesser General Public License and the program is freely available on the web. http://sashimi.svn.sourceforge.net/viewvc/sashimi/trunk/trans_proteomic_pipeline/src/Quantitation/Pepc.

摘要

未标记

在分析蛋白质组学数据时,确定两种条件下蛋白质丰度的生物学显著变化是一个关键问题。一种广泛使用的方法集中在光谱计数上,这是一种无标记的方法,它对分析中观察到的蛋白质的所有串联质谱进行求和。为了评估结果的显著性,我们最近结合 t 检验和 G 检验,进行随机排列分析,并从生物化学方面验证了这种方法。为了使统计方法自动化,我们开发了 PepC 软件程序,该程序在鉴定的差异表达蛋白数量和假发现率之间取得平衡。该工具可应用于广泛的蛋白质组数据集,使数据分析快速、可重复且易于被蛋白质组学专家和非专家解读。

可用性和实现

该软件是用 Java 编写的。它已添加到 Trans Proteomic Pipeline 项目的“Petunia”网络界面中,但也可以作为命令行程序运行。源代码为 GNU 较宽松公共许可证,程序可在网上免费获取。http://sashimi.svn.sourceforge.net/viewvc/sashimi/trunk/trans_proteomic_pipeline/src/Quantitation/Pepc。

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