SBEAMS Proteomics Tutorial

SBEAMS Proteomics Tutorial

SBEAMS – Proteomics Tutorial

Proteomics Course 2006-05-26

Eric Deutsch

Please follow along in this tutorial as we go through it in the class, or go your own pace if you choose. Feel free to add your own notes. If you make notes or have suggestions or bug reports that might be useful for others, please email them to .

  1. Login:
  2. Click “Login to SBEAMS”
  3. Login with the account informationprovided (classNN)
  4. Go to Proteomics Module Home Page (link on left nav bar) and test controls
  5. Current Project
  6. My Projects
  7. Accessible Projects
  8. Click on project names under “Accessible Projects” to switch current projects
  9. Explore several different projects
  10. Click on [View/Edit Full Project Information] hyperlink to view project attributes
  11. Click BACK and then [View/Edit Experiment Description] under Experiments.
  12. Explore the mmarelli – pxproteome project/experiment:
  13. Set the Current Project to mmarelli – pxproteome
  14. Click on [Proteomics Home] or [My Home] to get back to the top page
  15. View project and experiment attributes. READ the Experiment Description for “pxproteome” experiment! Some questions below assume you understand some of the ideas behind the experiment!
  16. Click on “Number of MS Runs: 14” (scroll down when page appears!!)
  17. Click on some TIC Plots in the table
  18. Click on some other hyperlinks in the table to look around
  19. Browse this dataset using hyperlinks on left navigation bar
  20. Choose Summarize Fractions
  21. Choose jranish – gricat experiment and QUERY (scroll down!)
  22. Choose Browse Search Hits
  23. Select mmarelli – pxproteome – YeastORF experiment
  24. P > 0.9
  25. QUERY
  26. Click on all hyper links across the table
  27. Re-sort by Xcorr descending. Re-sort by precursor m/z, % ACN, etc.
  28. Page through resultset
  29. View in Excel, TSV
  30. Make a continuous-value histogram of Precursor m/z, mass diff, % ACN
  31. Make a scatter plot of mass diff vs EstRT
  32. Click on the PA link for a protein and a peptide
  33. Choose Summarize over Proteins/Peptides
  34. Select mmarelli – pxproteome – YeastORF experiment
  35. P > 0.9
  36. QUERY
  37. In Display options, CTRL click to multi-select: [Group By Reference], [show GO Columns][Show SQL] and QUERY
  38. Click on all hyperlinks across the table
  39. At top, select [Full Detail], then near bottom set Gene Annototation Level to 2 and then [QUERY]
  40. At bottom choose [Discrete-value Histogram] and [Molecular Function] and do [VIEWRESULTSET] below the list boxes. Then scroll to bottom. Do another discrete-value histogram for [Cellular Component]
  41. Click on Display option [Group By Peptide] and QUERY
  42. Click on the 29 next to FOX2 LCTPTMPSNGTLK and examine
  43. Choose Compare Experiments
  44. Select jranish – gricat experiment
  45. Also CTRL Select mmarelli – pxproteome experiment
  46. QUERY
  47. Examine differences between experiments, and see summary table
  48. Find overlaps by selectingInput Form Format [Full Detail] and entering “>0” for both “# in Experiment 1” and “# in Experiment 2”. QUERY
  49. Select [Group by Peptides] and QUERY and examine
  50. Choose Compare Experiments to compare two search batches
  51. Select nbaliga – haloTEST – Mascot
  52. Also CTRL Select nbaliga – haloTEST – Sequest
  53. Set Probability >= 0.9
  54. Display Option: Group by peptide
  55. QUERY
  56. Examine differences between the two searches, and see summary table
  57. Choose Compare By Spec to compare two search batches by spectrum
  58. Select nbaliga – haloTEST – Mascot
  59. Also CTRL Select nbaliga – haloTEST – Sequest
  60. Probability in Experiment 1: >.95
  61. Probability in Experiment 2: <.5
  62. QUERY
  63. Examine resulting list
  64. Click on haloICAT2_33.1078.1078.3 and examine spectra
  65. Choose Browse Biosequences
  66. Select Yeast ORFs Database
  67. Type %perox% in Molecular Function Constraint field
  68. QUERY
  69. Choose Protein Summary (Protein Prophet output)
  70. Select mmarelli – pxproteome experiment
  71. Protein Group Probability >= 0.9 and Protein Probability >= 0.9
  72. QUERY
  73. Enter %perox% in cellular component and QUERY <no GO>
  74. Remove %perox% and reQUERY
  75. Re-sort by descending Protein Probabilty
  76. Download ResultSet in Format [Cytoscape]
  77. Within Cytoscape:
  78. Click {i} balloon
  79. Expand GO, Molecular Function
  80. Click on 3
  81. Click “Apply Annotation to all Nodes”
  82. Click on Go Molecular Function (level 3) on right
  83. Click Layout
  84. Expand Go Molecular Function (level 3) on right
  85. Click on individual GO categories and see them highlighted
  86. Click on “hydrolase” and then right click on graph and see attributes
  87. Exit Cytoscape. This afternoon will be all Cytoscape!
  1. Now use the interface to answer these questions:
  2. How many (GO-annotated) yeast peroxisomal proteins were identified in the pxproteome Protein Summary (i.e., by ProteinProphet)?
  • Of all the (GO-annotated) yeast peroxisomal proteins, how many were found in (use Compare Exps):
  • Pxproteomics
  • jranish-gricat
  • both
  • how many not seen at all? (hint: remove default “# of matches constraint”)
  • Why so few peroxisomal proteins in gricat?
  • Create a list of a few proteins not currently annotated as peroxisomal but that might be peroxisomal based on a comparison of identifications in pxproteome and gricat.
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