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Pathway	
  analysis	
  for	
  genomics	
  
Gary	
  Bader	
  
Oct.23.2012	
  –	
  FGED	
  Toronto	
  
Microtubule
Cytoskeleton
Cell Projection
& Cell Motility
Cell Proliferation
Glycosylation
Adhesion
Regulation of GTPase
Ki...
CorrelaBon	
  to	
  CausaBon	
  
•  GWAS:	
  find	
  geneBc	
  markers	
  correlated	
  with	
  
disease	
  –	
  powerful	
...
The Systems
Biology Pyramid
Cary, Bader, Sander, FEBS
Letters 579 (2005) 1815-20
Chris Sander, MSKCC
Cytoscape
cPath2
Path...
hWp://pathguide.org	
  
Vuk	
  Pavlovic	
  
Sylva	
  Donaldson	
  
>320	
  Pathway	
  
Databases!	
  
• Varied	
  formats,...
BioPAX	
  Pathway	
  Language	
  
•  Represent:	
  
– Metabolic	
  pathways	
  
– Signaling	
  pathways	
  
– Protein-­‐pr...
Emek Demir
SBGN.org
BioCarta
BioPAX
Aim: Convenient Access to Pathway Information
Facilitate	
  creaBon	
  and	
  communicaBon	
  of	
  pathway	
  data	
  
Ag...
Pathway	
  Commons:	
  cPath2	
  
•  hWp://www.pathwaycommons.org/pc2/	
  
Emek Demir, Igor Rodchenkov, Chris Sander Ozgun...
Network	
  
visualizaBon	
  
and	
  analysis	
  
UCSD,	
  ISB,	
  Agilent,	
  
MSKCC,	
  Pasteur,	
  UCSF,	
  
Unilever,	
...
Cytoscape	
  3	
  
•  Complete	
  re-­‐architecture:	
  OSGi	
  –	
  everything	
  is	
  an	
  app	
  
•  Enables	
  futur...
14	
  
hWp://cytoscapeweb.cytoscape.org/	
  
Chris;an	
  Tannus-­‐Lopes,	
  Max	
  Franz,	
  Yue	
  Dong	
  
	
  
Compound	
  Nodes	
  
Onur Sumer
Ugur Dogrusoz
Bilkent, Ankara
hCp://cytoscapeweb.cytoscape.org/demos/compound	
  
Cytoscape.js:	
  HTML5	
  –	
  iPad	
  
cytoscape.github.com/cytoscape.js/	
  
Gene Function Prediction
hWp://www.genemania.org	
  
Quaid Morris (Donnelly), Sara Mostafavi
Rashad Badrawi, Ovi Comes, Sy...
The	
  Factoid	
  Project	
  
•  Publishing	
  in	
  science	
  
–  Highly	
  inefficient	
  
–  Outdated	
  technology,	
  ...
Pathway	
  and	
  Network	
  Analysis	
  
1.  Gene	
  set:	
  pathway	
  
enrichment	
  analysis	
  
2.  Network:	
  netwo...
Increase Coverage and Depth
Cellular	
  Process	
  Representa;on	
  
•  Gene	
  set	
  
•  Network	
  
•  Process	
  model...
Acknowledgements	
  
Bader	
  Lab	
  
Domain	
  InteracBon	
  Team	
  
Chris	
  Tan	
  
Shirley	
  Hui	
  
Shobhit	
  Jain...
Gary bader fged_toronto_2012
Gary bader fged_toronto_2012
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Gary bader fged_toronto_2012

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Pathway analysis for genomics

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Transcript of "Gary bader fged_toronto_2012"

  1. 1. Pathway  analysis  for  genomics   Gary  Bader   Oct.23.2012  –  FGED  Toronto  
  2. 2. Microtubule Cytoskeleton Cell Projection & Cell Motility Cell Proliferation Glycosylation Adhesion Regulation of GTPase Kinase Activity/Regulation CNS Development Intellectual Disability Autism GTPase/Ras Signaling Regulation of cell proliferation Positive regulation of cell proliferation Tyrosin kinase Vasculature develepment Palate develepment Organ Morphogenesis Behavior Heart develepment RHO Ras Membrane Kinase regulation Cell Motility (stricter cluster) Centrosome Nucleolus Cell cycle Regulation of hormone levels Aminoacid derivative / amine metabolism Synaptic vescicle maturation Reelin pathway LIS1 in neuronal migration and development Negative regulation of cell cycle cKIT pathwaymTor pathway Zn finger domain Carboxyl esterase domain Ras signaling GTPase regulator Neuron migration Cell Motility (stricter cluster) Cell morphogenesis Cell projection organization CNS development Brain development Neurite development CNS neuron differentiation Axonogenesis Projection neuron axonogenesis Cerebral cortex cell migration SMC flexible hinge domain Urea and amine group metabolism MHC-I Zoom of CNS-Development ID ID ASDASD Both 0% 12.5% Enriched in deletions FDR Known disease genes Enriched only in disease genes Node type (gene-set) Edge type (gene-set overlap) From disease genes to enriched gene-sets Between gene-sets enriched in deletions Between sets enriched in deletions and in disease genes or between disease sets only Pinto  et  al.  FuncBonal  impact  of  global  rare  copy  number  variaBon  in  auBsm   spectrum  disorders.  Nature.  2010  Jun  9.  
  3. 3. CorrelaBon  to  CausaBon   •  GWAS:  find  geneBc  markers  correlated  with   disease  –  powerful  approach,  but:   – genomics  reduces  staBsBcal  power  (>mulBple   tesBng  correcBon  with  >SNPs)   – rare  variants  =  more  samples   •  Associate  pathways  to  increase  power   – Fewer  pathways,  organize  many  rare  variants   (damaging  the  system  causes  the  disease)   •  Use  pathway  knowledge  to  idenBfy  potenBal   disease  causes  
  4. 4. The Systems Biology Pyramid Cary, Bader, Sander, FEBS Letters 579 (2005) 1815-20 Chris Sander, MSKCC Cytoscape cPath2 Pathway Commons BioPAX
  5. 5. hWp://pathguide.org   Vuk  Pavlovic   Sylva  Donaldson   >320  Pathway   Databases!   • Varied  formats,  representa;on,  coverage   • Pathway  data  extremely  difficult  to  combine   and  use  
  6. 6. BioPAX  Pathway  Language   •  Represent:   – Metabolic  pathways   – Signaling  pathways   – Protein-­‐protein,  molecular  interacBons   – Gene  regulatory  pathways   – GeneBc  interacBons   •  Community  effort:  pathway  databases  distribute   pathway  informaBon  in  standard  format   www.biopax.org  
  7. 7. Emek Demir SBGN.org BioCarta BioPAX
  8. 8. Aim: Convenient Access to Pathway Information Facilitate  creaBon  and  communicaBon  of  pathway  data   Aggregate  pathway  data  in  the  public  domain   Provide  easy  access  for  pathway  analysis   Long  term:  Converge   to  integrated  cell  map   hCp://pathwaycommons.org  
  9. 9. Pathway  Commons:  cPath2   •  hWp://www.pathwaycommons.org/pc2/   Emek Demir, Igor Rodchenkov, Chris Sander Ozgun Babur, Arman Aksoy, Onur Sumer, Ethan Cerami, Ben Gross
  10. 10. Network   visualizaBon   and  analysis   UCSD,  ISB,  Agilent,   MSKCC,  Pasteur,  UCSF,   Unilever,  UToronto,  U   Texas   hWp://cytoscape.org   Pathway  comparison   Literature  mining   Gene  Ontology  analysis   AcBve  modules   Complex  detecBon   Network  moBf  search  
  11. 11. Cytoscape  3   •  Complete  re-­‐architecture:  OSGi  –  everything  is  an  app   •  Enables  future  features:   –  More  stable  and  powerful  APIs   –  ScripBng,  macros,  recordable  history,  beWer  undo/redo   –  Command  line  mode,  good  for  use  on  compute  clusters   –  InteracBve  control  from  other  scripBng  languages  e.g.  R   •  Fixing  bugs  and  porBng  plugins   •  3.0  beta  now  available   –  Mirror  funcBonality  in  2.8   –  Encourage  plugin  to  app  porBng   –  hWp://www.cytoscape.org/cy3.html  
  12. 12. 14   hWp://cytoscapeweb.cytoscape.org/   Chris;an  Tannus-­‐Lopes,  Max  Franz,  Yue  Dong    
  13. 13. Compound  Nodes   Onur Sumer Ugur Dogrusoz Bilkent, Ankara hCp://cytoscapeweb.cytoscape.org/demos/compound  
  14. 14. Cytoscape.js:  HTML5  –  iPad   cytoscape.github.com/cytoscape.js/  
  15. 15. Gene Function Prediction hWp://www.genemania.org   Quaid Morris (Donnelly), Sara Mostafavi Rashad Badrawi, Ovi Comes, Sylva Donaldson, Max Franz, Christian Lopes, Farzana Kazi, Jason Montojo, Harold Rodriguez, Khalid Zuberi •   Guilt-­‐by-­‐associaBon  principle   •   Biological  networks  are  combined  intelligently  to   opBmize  predicBon  accuracy   •   Algorithm  is  more  fast  and  accurate  than  its   peers   Mostafavi  S  et  al.  Genome  Biol.  2008;9  Suppl  1:S4   Warde-­‐Farley  D  et  al.  Nucleic  Acids  Res.  2010  Jul; 8:W214-­‐20.  
  16. 16. The  Factoid  Project   •  Publishing  in  science   –  Highly  inefficient   –  Outdated  technology,  difficult  to  search  and  compute   •  hWp://www.elseviergrandchallenge.com/   –  Winner:  hWp://reflect.ws/   •  Pathway  and  network  informaBon  database   curaBon   –  Highly  inefficient   •  The  factoid  project   Max  Franz,  Igor  Rodchenkov,  Ozgun  Babur,  Emek  Demir,  Chris  Sander  
  17. 17. Pathway  and  Network  Analysis   1.  Gene  set:  pathway   enrichment  analysis   2.  Network:  network  regions   (modules),  regulaBon   3.  Process  model:  classical   pathways   4.  SimulaBon  model:  detailed   models   Mechanistic Understanding GenomeCoverage Anduse
  18. 18. Increase Coverage and Depth Cellular  Process  Representa;on   •  Gene  set   •  Network   •  Process  model   •  SimulaBon  model   •  Analysis  methods  need  to   keep  up   Coverage Depth Depth Data and analysis methods Present Future Km=3.0×10−4
  19. 19. Acknowledgements   Bader  Lab   Domain  InteracBon  Team   Chris  Tan   Shirley  Hui   Shobhit  Jain   Brian  Law   Jüri  Reimand     Former:   David  Gfeller   Xiaojian  Shao   Funding   hWp://baderlab.org   www.GeneMANIA.org Quaid Morris (Donnelly) Rashad Badrawi, Ovi Comes, Sylva Donaldson, Christian Lopes, Farzana Kazi, Jason Montojo, Sara Mostafavi, Harold Rodriguez, Khalid Zuberi Gene;c  Intx,  Pathways:   Anastasia  Baryshnikova   Iain  Wallace   Magali  Michaut   Ron  Ammar   Daniele  Merico   Ruth  Isserlin   Vuk  Pavlovic   Igor  Rodchenkov   Pathway  Commons   Chris  Sander   Ethan  Cerami   Ben  Gross   Emek  Demir   Igor  Rodchenkov   Nadia  Anwar   Ozgun  Babur  
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