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Proteome Analyst

Proteome Analyst. Transparent High-throughput Protein Annotation: Function, Localization and Custom Predictors. Proteome Analyst. Duane Szafron, Paul Lu, Russell Greiner, David Wishart, Zhiyong Lu, Brett Poulin, Roman Eisner, John Anvik,Cam Macdonell. Proteome Analyst. Proteome

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Proteome Analyst

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  1. Proteome Analyst Transparent High-throughput Protein Annotation: Function, Localization and Custom Predictors

  2. Proteome Analyst Duane Szafron, Paul Lu, Russell Greiner, David Wishart, Zhiyong Lu, Brett Poulin, Roman Eisner, John Anvik,Cam Macdonell

  3. Proteome Analyst • Proteome • one of many ‘-omes’ • set of all proteins in an organism • Analysis • prediction of protein function or localization from sequence data

  4. Analyze a Protein • We have examples of annotated proteins in various protein classes. • We have more examples of unannotated proteins.

  5. Analyze a Protein • We have examples of annotated proteins in various protein classes. • We have more examples of unannotated proteins. • What do we do?

  6. Analyze a Protein • We have examples of annotated proteins in various protein classes. • We have more examples of unannotated proteins. • What do we do? • Find homologues to each protein and assume similar function.

  7. Analyze a Protein • We have examples of annotated proteins in various protein classes. • We have more examples of unannotated proteins. • What do we do? • Find homologues to each protein and assume similar function. • Find characteristics of each protein that affect function.

  8. Analyzing Proteins • One Protein?

  9. Analyzing Proteins • One Protein? • Just do it.

  10. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins?

  11. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins? • Post-doc familiar with protein classes.

  12. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins? • Post-doc familiar with protein classes. • 50 Proteins?

  13. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins? • Post-doc familiar with protein classes. • 50 Proteins? • grad student

  14. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins? • Post-doc familiar with protein classes. • 50 Proteins? • grad student • 5000 proteins?

  15. Analyzing Proteins • One Protein? • Just do it. • 5 Proteins? • Post-doc familiar with protein classes. • 50 Proteins? • grad student • 5000 proteins? • summer students

  16. Proteome Analyst

  17. Proteome Analyst • High-throughput • Transparent • Prediction of • Protein Function • Protein Localization • Custom Classification

  18. Machine Learning Task • Training • INPUT: sequences, classes • OUTPUT: Classifier • Analysis • INPUT: sequences, Classifier • OUTPUT: classes

  19. Machine Learning Task • Training • INPUT: sequences, classes • OUTPUT: Classifier • Analysis • INPUT: sequences, Classifier • OUTPUT: classes, explanation

  20. Training • INPUT • sequences, classes • PA Tools • sequences  features • ML Algorithm • features, classes  Classifier • OUTPUT • Classifier

  21. Training: INPUT >class A<Training Seq 1 MVGSGLLWLALVSCILTQASAVQRGYGN PIEASSYGL... >class B<Training Seq 2 LLDEPFRSTENSAGSQGCDKNMSGWYRF VGEGGVRMS... >class B<Training Seq 3 EVIAYLRDPNCSSILQTEERNWVSVTSP VQASACRNI... . . .

  22. Training: INPUT classes >class A<Training Seq 1 MVGSGLLWLALVSCILTQASAVQRGYGN PIEASSYGL... >class B<Training Seq 2 LLDEPFRSTENSAGSQGCDKNMSGWYRF VGEGGVRMS... >class B<Training Seq 3 EVIAYLRDPNCSSILQTEERNWVSVTSP VQASACRNI... . . . protein sequences

  23. Training: PA Tools • sequences  features

  24. Training: PA Tools • sequences  features • Homology Tools (BLAST) • sequence  homologues • homologues  annotations • annotations  features

  25. Homology Tool • sequence  features sequence seq DB BLAST homologues retrieve parse annotations features

  26. Homology Tool • sequence  features sequence DBSOURCE swissprot: locus MPPB_NEUCR, ... xrefs (non-sequence databases): ... InterProIPR001431,... KEYWORDS Hydrolase; Metalloprotease; Zinc; Mitochondrion; Transit peptide; Oxidoreductase; Electron transport; Respiratory chain. seq DB BLAST homologues retrieve parse annotations features

  27. Homology Tool • sequence  features sequence seq DB BLAST homologues retrieve parse annotations features

  28. Training: PA Tools • sequences  features • Homology Tools (BLAST) • sequence  homologues • homologues  annotations • annotations  features • Pattern Tools (PFAM, ProSite, …) • sequences  motifs • motifs  features

  29. Pattern Tool • sequence  features sequence pattern DB find patterns parse features

  30. Pattern Tool • sequence  features sequence pattern DB find Pfam; PF00234; tryp_alpha_amyl; 1. PROSITE; PS00940; GAMMA_THIONIN; 1. PROSITE; PS00305; 11S_SEED_STORAGE; 1. patterns parse features

  31. Pattern Tool • sequence  features • not included in current results sequence pattern DB find patterns parse features

  32. Training: ML Algorithm • features, classes  Classifier

  33. Training: ML Algorithm • features, classes  Classifier • any ML Algorithm may be used • default = naïve Bayes • consistently near-best accuracy (SVM, ANN slightly better) • efficient (for high-throughput) • easy to interpret

  34. Training: OUTPUT • Classifier

  35. Analysis (Classification) • INPUT • sequences • PA Tools • sequences  features • Classifier • features  classes, explanation • OUTPUT • classes

  36. Analysis: INPUT >Seq 1 DTILNINFQCAYPLDMKVSLQAALQPIV SSLNVSVDG... >Seq 2 AVELSVESVLYVGAILEQGDTSRFNLVL RNCYATPTE... >Seq 3 HVEENGQSSESRFSVQMFMFAGHYDLVF LHCEIHLCD... . . .

  37. Analysis: INPUT >Seq 1 DTILNINFQCAYPLDMKVSLQAALQPIV SSLNVSVDG... >Seq 2 AVELSVESVLYVGAILEQGDTSRFNLVL RNCYATPTE... >Seq 3 HVEENGQSSESRFSVQMFMFAGHYDLVF LHCEIHLCD... . . . protein sequences

  38. Analysis: PA Tools • sequences  features

  39. Analysis: PA Tools • sequences  features • Homology Tools (BLAST) • sequence  homologues • homologues  annotations • annotations  features • Pattern Tools (PFAM, ProSite, …) • sequences  motifs • motifs  features

  40. Analysis: Classification • features  classes

  41. Analysis: Classification • features  classes • naïve Bayes • returns probabilities of each class for each sequence • efficient (for high-throughput) • easy to interpret

  42. Analysis: Classification • features  classes, explanation

  43. Analysis: Classification • features  classes, explanation

  44. Analysis: Classification • features  classes, explanation

  45. Analysis: Classification • features  classes, explanation

  46. Analysis: Classification • features  classes, explanation

  47. Results: General Function • GeneQuiz classification • 5-fold x-val accuracy on 14 classes

  48. Results: General Function • GeneQuiz classification • 5-fold x-val accuracy on 14 classes

  49. Results: Specific Function • K+ Ion Channel Proteins • 5-fold x-val accuracy on 78 sequences, 4 classes

  50. Results: Specific Function • K+ Ion Channel Proteins • 5-fold x-val accuracy on 78 sequences, 4 classes

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