Discover true association rates in multi-protein complex proteomics data sets

Changyu Shen, Lang Li, Jake Yue Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Experimental processes to collect and process proteomics data are increasingly complex, while the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed a complete empirical Bayes model to analyze multi-protein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Our model considers not only bait-prey associations, but also prey-prey associations missed in previous work. Using our model and a yeast MPC proteomics data set, we estimated that there should be an average of 28 true associations per MPC, almost ten times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%.

Original languageEnglish (US)
Title of host publicationProceedings - 2005 IEEE Computational SystemsBioinformatics Conference, CSB 2005
Pages167-174
Number of pages8
DOIs
StatePublished - Dec 1 2005
Event2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005 - Stanford, CA, United States
Duration: Aug 8 2005Aug 11 2005

Publication series

NameProceedings - 2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005
Volume2005

Other

Other2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005
CountryUnited States
CityStanford, CA
Period8/8/058/11/05

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ASJC Scopus subject areas

  • Engineering(all)
  • Medicine(all)

Cite this

Shen, C., Li, L., & Chen, J. Y. (2005). Discover true association rates in multi-protein complex proteomics data sets. In Proceedings - 2005 IEEE Computational SystemsBioinformatics Conference, CSB 2005 (pp. 167-174). [1498018] (Proceedings - 2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005; Vol. 2005). https://doi.org/10.1109/CSB.2005.29