1 / 23

Yoona Kim University of California, San Diego

MaxQuant enables high peptide identification rates, individualized p.p.b. -range mass accuracies and proteome-wide protein quantification. Yoona Kim University of California, San Diego. UCSD Mass Spectrometry Journal Club 12/03/10. MaxQuant. Outline.

gladys
Download Presentation

Yoona Kim University of California, San Diego

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification Yoona Kim University of California, San Diego UCSD Mass Spectrometry Journal Club 12/03/10

  2. MaxQuant

  3. Outline • What is the MaxQuant? • What’s benefits from MaxQuant? • Conclusion • Critisism

  4. What is the MaxQuant?

  5. Stable amino acid isotope-labeled (SILAC) (1)

  6. Stable amino acid isotope-labeled (SILAC) (2)

  7. MaxQuant’s pipeline

  8. 1. Feature detection and peptide quantitation-Peak Detection (1) • 2D peaks • 3D peaks

  9. 1. Feature detection and peptide quantitation-Peak Detection (2) • A bootstrap estimation over B = 150 ∵unknown atomic composition and intensity profiles overlap

  10. 1. Feature detection and peptide quantitation-SILAC pair detection (1) • Step 1: All possible pairs of isotope patterns • The correlation test >0.5 • Have equal charge, close enough in mass • Step 2 : Convolute two isotope patterns • K, R, KK, KR, RR, KKK, KKR, KRR, and RRR • Find the same atomic composition

  11. 1. Feature detection and peptide quantitation-SILAC pair detection (2) • Ex. The peptide contains one K and no R • Heavy isotope labeled form ,

  12. 1. Feature detection and peptide quantitation-SILAC pair detection (3)

  13. 3. Identification and validation • Posterior Error Probability - for calculating the false-discovery rate

  14. 3. Identification and validation–Peptide score distributions

  15. What’s the benefits from MaxQuant?

  16. 1. Improving peptide mass accuracy

  17. 2. High rate of identified MS/MS spectra

  18. 3. Proteome-wide protein quantifiation • Protein ratio = median(all SILAC peptide ratio) • P-value for detection of significant outlier ratio (significance A)

  19. 3. Proteome-wide protein quantifiation Significance A Significance B

  20. Conclusion • MaxQuant improves • Peptide identification rates • Peptide mass accuracy • Proteom-wide protein quantification

  21. Critisism • All experimental results are based on Mascot search • Mascot does not fully benefit from high-accuracy (limit 0.25Da) -> It is not working…!! (Sangtae said)

  22. IF you have more questions….. Go MaxQunt summer school It will be fun!!!

More Related