Yoona Kim University of California, San Diego UCSD Mass Spectrometry Journal Club 12/03/10.

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Presentation transcript:

Yoona Kim University of California, San Diego UCSD Mass Spectrometry Journal Club 12/03/10

MaxQuant

 What is the MaxQuant?  What’s benefits from MaxQuant?  Conclusion  Critisism

Input : High resolution, quantitative MS data of SILAC- encoded cell populations MaxQuant Output: Identified MS/MS spectra and protein quantification graph(x=protein ration/y=intensity)

4. Visualization 3. Identification and validation 2. MS/MS Ion search - Mascot 1. Feature detection and peptide quantitation

 2D peaks  3D peaks

 A bootstrap estimation over B = 150 ∵ unknown atomic composition and intensity profiles overlap

 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

 Ex. The peptide contains one K and no R - Heavy isotope labeled form,

 Posterior Error Probability - for calculating the false-discovery rate

1. Improving peptide mass accuracy 2. High rate of identified MS/MS spectra3. Proteome-wide protein quantifiation

 Protein ratio = median(all SILAC peptide ratio)  P-value for detection of significant outlier ratio (significance A)

Significance ASignificance B

 MaxQuant improves ◦ Peptide identification rates ◦ Peptide mass accuracy ◦ Proteom-wide protein quantification

 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)

Go MaxQunt summer school It will be fun!!!