Combining so as to enhance Affectability Results from Numerous Hunt Philosophies.


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Combining so as to enhance Affectability Results from Various Hunt Strategies . Brian C. Searle Proteome Programming Inc. Portland, OR Brian.Searle@ProteomeSoftware.com MBI workshop on Computational Proteomics and Mass Spectrometry (January 11-14, 2005) . The Investigative Test.
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Combining so as to enhance Sensitivity Results from Multiple Search Methodologies Brian C. Searle Proteome Software Inc. Portland, OR Brian.Searle@ProteomeSoftware.com MBI workshop on Computational Proteomics and Mass Spectrometry (January 11-14, 2005)

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The Analytical Challenge Biological Samples Control Experiments Q-TOF Unknown Spectra IonTrap

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The Analytical Challenge Why would you be able to just decipher half as much MS/MS information in examinations you really think about? What is going ahead with the staying 90% unidentified spectra?

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The OpenSea Approach De Novo Sequence: YD[Cc]DD[220]GADHFTY[200]R OpenSea Alignment: Crystallin,  S (CRBS_HUMAN) GRRYD(Cc)D(Cc)( D )(Cc)AD(FH)TY( LS )RCNS || | X || | || | YD(Cc)D(D )([220])(G )AD(HF)TY([200])R

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all over again Sequence YD[Cc]DD[220]GADHFTY[200]R 163-115-160-115-115-220-57-71-…

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anew Sequence … YD[Cc]DD[220]GADHFTY[200]R 163-115-160-115-115-220-57-71-… G-57 R-156 R-156 Y-163 D-115 C-160 D-115 C-160 D-115 C-160 A-71 Database Sequence …

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once more Sequence … YD[Cc]DD[220]GADHFTY[200]R 163-115-160-115-115-220-57-71-… G-57 R-156 R-156 Y-163 D-115 C-160 D-115 C-160 D-115 C-160 A-71 Database Sequence …

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Auto-Interpretation of OpenSea Results OpenSea Alignment: GRRYD(Cc)D (Cc)( D )(Cc) AD(FH)TY( LS )RCNS || | X || | || | YD(Cc)D (D )([220])(G ) AD(HF)TY([200])R +14 AMU on either cysteine or - 43 AMU on aspartic acid… Modification lookup table proposes methylation of cysteine! Auto-Interpretation: GRRYD(Cc)D( CmDCc )AD(FH)TY( LS )RCNS || | : || | || | YD(Cc)D( D[220]G )AD(HF)TY([200])R

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Spectrum Identification Overlap Between Search Methods SEQUEST 6% 17% 7% 41% X!Tandem 10% OpenSea PTMs polymorphisms 9%

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Spectrum Identification Overlap Between Search Methods SEQUEST nonpartisan misfortunes 6% 17% 7% 41% X!Tandem semi-tryptic no stepping stool 10% OpenSea 9%

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Scaffold Data Compiler Combine SEQUEST, Mascot, X!Tandem, and OpenSea results Utilize range grouping and clamor channels to uproot uninteresting spectra Export intriguing, unidentified spectra for further investigation Search Wider Drill Deeper Remove Junk Focus Efforts Combine Database Searching IDs Cluster Spectra to Previously IDs Report Interesting, Unidentified Spectra Filter Electronic Noise For All Spectra

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Combining SEQUEST and X!Tandem Scores X!Tandem –log(E-Value) Score SEQUEST Descriminant Score (Peptide Prophet, ISB)

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Combining SEQUEST and X!Tandem Scores X!Tandem –log(E-Value) Score SEQUEST Descriminant Score (Peptide Prophet, ISB)

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Peptide Prophet (ISB) Incorrect IDs p=50% Correct IDs

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Protein Prophet (ISB) Protein 1 Protein 7 Peptide 1 Protein 4 Peptide 2 Peptide 3 Protein 2 Protein 8 Peptide 4 Protein 5 Peptide 5 Protein 3 Peptide 6 Protein 6 Peptide 7

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Protein Prophet (ISB) Protein 1 Protein 7 Peptide 1 Protein 4 Peptide 2 Peptide 3 Protein 2 Protein 8 Peptide 4 Protein 5 Peptide 5 Protein 3 Peptide 6 Protein 6 Peptide 7

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Incorrect IDs p(NSP|-) Correct IDs p(NSP|+) Normalized Distribution For each spectrum… IDs with: high NSP- - p Low NSP- - p NSP Bin Number Log p(NSP|+)/p(NSP|-) Correct IDs have higher NSP Values

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Peptide Prophet Protein Prophet Get SEQUEST IDs Calculate SEQUEST Probability Get Mascot IDs Calculate Mascot Probability Calculate Combined Peptide Probability For Each Spectrum Calculate Protein Probabilities Get X!Tandem IDs Calculate X!Tandem Probability Scaffold Merge Prophet Get OpenSea IDs Calculate OpenSea Probability …

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Peptide 1 Get SEQUEST Identification p=85% p=76% Get Mascot Identification Peptide 2 For Each Spectrum Get X!Tandem Identification p=54% Peptide 3 Get OpenSea Identification

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Peptide 1 Get SEQUEST Identification Peptide 4 p=27% Get Mascot Identification Peptide 2 p=81% For Each Spectrum Peptide 5 Get X!Tandem Identification p=35% Peptide 3 Get OpenSea Identification

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Peptide 1 Peptide 7 Get SEQUEST Identification Peptide 4 Get Mascot Identification Peptide 2 Peptide 8 For Each Spectrum Peptide 5 Get X!Tandem Identification Peptide 3 Peptide 6 Get OpenSea Identification

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Protein Prophet’s NSP quality (number of kin peptides) becomes… Merge Prophet’s number of kin projects

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Incorrect IDs p(NSP|-) Correct IDs p(NSP|+) Normalized Distribution For each spectrum… IDs with: high NSP- - p Low NSP- - p NSP Bin Number Log p(NSP|+)/p(NSP|-) Correct IDs have higher NSP Values

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Accuracy of the Probability Combining Model Mascot X!Tandem Calculated Probability Combination SEQUEST Actual Probability

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Percentage of QTOF Spectra Correctly Identified as Control Proteins Identified By SEQUEST (40%) Unknown Spectra (60%)

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Percentage of QTOF Spectra Correctly Identified as Control Proteins Identified By Scaffold (60%) Unknown Spectra (40%)

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Percentage of QTOF Spectra Correctly Identified as Control Proteins Identified By Scaffold (73%) Unknown Spectra (27%)

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#1 #2

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#1 #2

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#1 #2

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#1 #2

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#2 #3

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Protein Prophet Find Spectra Similar to Previously Identified Report Interesting, Unidentified Spectra Calculate Combined Probability Calculate Protein Probabilities Filter Electronic Noise Scaffold Merge Prophet Scaffold Cluster Prophet

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Cluster Prophet Principle If a unidentified range is 95% like an accurately distinguished spectrum… it is additionally thought to be recognized.

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Rank-Based Cluster Similarity Score Incorrect IDs p=50% Correct IDs

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MS/MS Spectrum Filter Dynamic extent channel expels spectra from peptides with poor/no discontinuity Signal to clamor channel evacuates electronic commotion

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Percentage of QTOF Spectra Correctly Identified as Control Proteins Identified By Scaffold (73%) Unknown Spectra (27%)

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Percentage of QTOF Spectra Correctly Identified as Control Proteins Identified By Scaffold (74%) Unknown Spectra (5%) Not Interesting (21%)

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Percentage of 2D-LC QTOF Spectra Correctly Identified as Lens Proteins Identified By Scaffold (48%) Unknown Spectra (21%) Not Interesting (31%)

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The Analytical Challenge Biological Samples Control Experiments IDed by SEQUEST IDed by SEQUEST Q-TOF Unknown Spectra Unknown Spectra IDed by SEQUEST IDed by SEQUEST IonTrap Unknown Spectra Unknown Spectra

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The Analytical Challenge Biological Samples Control Experiments IDed by Scaffold IDed by Scaffold Q-TOF Unknown Spectra Unknown Spectra 85% more IDs 95% appreciation 336% more IDs 79% perception IDed by Scaffold IDed by Scaffold IonTrap Unknown Spectra Unknown Spectra 48% more IDs 65% understanding 227% more IDs 75% cognizance

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Conclusions Using Scaffold advancements, you can bore more profound and hunt more extensive utilizing different database seeking methodologies and MS/MS range grouping Scaffold and executions of Peptide/Protein Prophet were composed in stage autonomous Java Scaffold will be accessible at ASMS 2005

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OpenSea Team (OHSU) Srinivasa Nagalla Surendra Dasari Ashok Reddy Larry David Phil Wilmarth Ashley McCormack Contact: nagallas@ohsu.edu Scaffold Team (Proteome Software Inc.) Mark Turner James Brundege Contact: Brian.Searle@ ProteomeSo

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