期刊
JOURNAL OF PROTEOME RESEARCH
卷 14, 期 10, 页码 4118-4126出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b00183
关键词
proteomics; label-free mass spectrometry; quantitative analysis; statistical methods; reproducibility; ROTS
资金
- JDRF [2-2013-32]
- Paivikki and Sakari Sohlberg Foundation
- Sigrid Juselius foundation
- Nord-Forsk (Nordic QP: Nordic Education Network for Quantitative Proteomics) [070178]
As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as real experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据