Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Psb tutorial cancer_pathways

1,271 views

Published on

Pacific Symposium on Biocomputing (PSB) 2015 Tutorial for Cancer Pathways: Automatic Extraction, Representation, and Reasoning in the Big Data Era

Published in: Science
  • DOWNLOAD THIS BOOKS INTO AVAILABLE FORMAT (2019 Update) ......................................................................................................................... ......................................................................................................................... Download Full PDF EBOOK here { https://soo.gd/irt2 } ......................................................................................................................... Download Full EPUB Ebook here { https://soo.gd/irt2 } ......................................................................................................................... Download Full doc Ebook here { https://soo.gd/irt2 } ......................................................................................................................... Download PDF EBOOK here { https://soo.gd/irt2 } ......................................................................................................................... Download EPUB Ebook here { https://soo.gd/irt2 } ......................................................................................................................... Download doc Ebook here { https://soo.gd/irt2 } ......................................................................................................................... ......................................................................................................................... ................................................................................................................................... eBook is an electronic version of a traditional print book THIS can be read by using a personal computer or by using an eBook reader. (An eBook reader can be a software application for use on a computer such as Microsoft's free Reader application, or a book-sized computer THIS is used solely as a reading device such as Nuvomedia's Rocket eBook.) Users can purchase an eBook on diskette or CD, but the most popular method of getting an eBook is to purchase a downloadable file of the eBook (or other reading material) from a Web site (such as Barnes and Noble) to be read from the user's computer or reading device. Generally, an eBook can be downloaded in five minutes or less ......................................................................................................................... .............. Browse by Genre Available eBooks .............................................................................................................................. Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, ......................................................................................................................... ......................................................................................................................... .....BEST SELLER FOR EBOOK RECOMMEND............................................................. ......................................................................................................................... Blowout: Corrupted Democracy, Rogue State Russia, and the Richest, Most Destructive Industry on Earth,-- The Ride of a Lifetime: Lessons Learned from 15 Years as CEO of the Walt Disney Company,-- Call Sign Chaos: Learning to Lead,-- StrengthsFinder 2.0,-- Stillness Is the Key,-- She Said: Breaking the Sexual Harassment Story THIS Helped Ignite a Movement,-- Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones,-- Everything Is Figureoutable,-- What It Takes: Lessons in the Pursuit of Excellence,-- Rich Dad Poor Dad: What the Rich Teach Their Kids About Money THIS the Poor and Middle Class Do Not!,-- The Total Money Makeover: Classic Edition: A Proven Plan for Financial Fitness,-- Shut Up and Listen!: Hard Business Truths THIS Will Help You Succeed, ......................................................................................................................... .........................................................................................................................
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here

Psb tutorial cancer_pathways

  1. 1. Translational Genomics Research Institute | www.tgen.org Cancer Pathway Analysis and Personalized Medicine Jeff  Kiefer   Research  Associate  Inves4gator   Transla4onal  Genomics  Research   Ins4tute
  2. 2. Translational Genomics Research Institute | www.tgen.org Big Cancer Data Resources and Secondary Data Tools Pathway Analysis - Resources, Methods, and Tools Personalized Medicine - ‘Interpretation bottleneck’ Drug to Genomic Event Matching Outline
  3. 3. Translational Genomics Research Institute | www.tgen.org Cancer Genome Data Repositories https://www.ebi.ac.uk/arrayexpress/ http://www.ncbi.nlm.nih.gov/geo/ http://cancergenome.nih.gov/ https://icgc.org/
  4. 4. Translational Genomics Research Institute | www.tgen.org Cancer Genome Data Repositories and Data Portals https://genome-cancer.ucsc.edu/ http://www.cbioportal.org/public-portal/ http://cancergenome.broadinstitute.orgTumorPortal https://dcc.icgc.org/ http://genomeportal.stanford.edu/pan-tcga http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/
  5. 5. Translational Genomics Research Institute | www.tgen.org http://www.cbioportal.org/public-portal/
  6. 6. Translational Genomics Research Institute | www.tgen.org http://www.cbioportal.org/public-portal/
  7. 7. Translational Genomics Research Institute | www.tgen.org Pathways Analysis Pathway analysis encompasses a number of different approaches and methods applied to large-scale -omic data sets. The goal is to discover meaningful biological knowledge from large data sets often in the form of a gene list. Pathway is a term that describes a step-wise signal transduction pathway. However, the term ‘pathway’ is also loosely used to encompass genes sets derived from signatures or other biological processes such as the gene ontology.
  8. 8. Translational Genomics Research Institute | www.tgen.org (2012). PLOS Computational Biology, 8(2), e1002375. doi:10.1371/journal.pcbi.1002375.t001 Pathways Analysis Good general review outlining techniques, resources, and issues in pathway analysis
  9. 9. Translational Genomics Research Institute | www.tgen.org Pathways Analysis Threshold-Based = Enrichment analysis performed on a gene list derived from statistical test. Non-threshold Based = All data is used. First popularized by gene set enrichment analysis (GSEA). ‘de-novo’ Based = Pathways or gene sets derived from primary data.
  10. 10. Translational Genomics Research Institute | www.tgen.org Pathway Resources http://www.reactome.org/ http://www.genome.jp/kegg/pathway.html http://www.broadinstitute.org/gsea/msigdb/index.jsp Commercial Resources http://www.pathwaycommons.org/about/#main-container
  11. 11. Translational Genomics Research Institute | www.tgen.org Threshold-based Pathway Enrichment Tools https://toppgene.cchmc.org/ http://amp.pharm.mssm.edu/Enrichr http://www.ici.upmc.fr/cluego/
  12. 12. Translational Genomics Research Institute | www.tgen.org ToppGene extensive pathway gene sets available for enrichment analysis
  13. 13. Translational Genomics Research Institute | www.tgen.org Easy to use web interface Add list of gene identifiers to perform enrichment analysis on.
  14. 14. Translational Genomics Research Institute | www.tgen.org Results sorted based on significance.
  15. 15. Translational Genomics Research Institute | www.tgen.org
  16. 16. Translational Genomics Research Institute | www.tgen.org Results Gene Set/Pathway Categories
  17. 17. Translational Genomics Research Institute | www.tgen.org Different Result Outputs
  18. 18. Translational Genomics Research Institute | www.tgen.org http://www.ici.upmc.fr/cluego/ ClueGO integrates Gene Ontology (GO) terms as well as pathways and creates a functionally organized GO/ pathway term network. COL9A1 COL28A1 COL14A1 COL9A3 COL20A1 COL12A1 COL9A2 Collagen biosynthesis and modifying enzymes Collagen formation forebrain development SEMA3A SYPL2 FGF9 CNTNAP2 SLC6A4 NDNF SLC5A3 HEPH SLC14A1 Transport of glucose and other sugars, bile salts and organic acids, metal ions and amine compounds RHBG SLC6A20 TBX5 RAC3 negative regulation of cell differentiation negative regulation of Wnt signaling pathway BICC1 PRICKLE1 DKK1 SFRP2 EFEMP1 regulation of cell development COL1A1 EPHA3 SLIT2 FES APCDD1SULF1 PPP2R3A regulation of canonical Wnt signaling pathway regulation of Wnt signaling pathway DDR2 LTF regulation of cell differentiation SP7 MT3 BAX S100A9 S100A8 NDUFA13 regulation of cysteine-type endopeptidase activity involved in apoptotic process BBC3 regulation of intrinsic apoptotic signaling pathway IGFBP3 MEGF10 SLN CACNG4 CCL4 CACNB2 ENPP1 KCNH2 regulation of ion transport positive regulation of ion transport CCL3 CTLA4 SCN4B GADD45G TRIB3 intrinsic apoptotic signaling pathway p53 signaling pathway BAI1 SEPT4 CD82 SFN TLR4 osteoblast differentiation TLR3 Rheumatoid arthritis IL8 LOC100509457 CXCL5 ANGPT1 Toll-like receptor signaling pathway CTSK RUNX2 Cytoscape App
  19. 19. Translational Genomics Research Institute | www.tgen.org Non-Threshold Pathway Enrichment Tools http://www.broadinstitute.org/gsea/index.jsp
  20. 20. Translational Genomics Research Institute | www.tgen.org GSEA Can be accessed through a number of resources and methods Java Desktop R-GSEA Gene Pattern
  21. 21. Translational Genomics Research Institute | www.tgen.org GSEA Use Case Anaplastic Thyroid Cancer vs Non-Tumor Thyroid
  22. 22. Translational Genomics Research Institute | www.tgen.org GSEA Use Case
  23. 23. Translational Genomics Research Institute | www.tgen.org GSEA Visualization with Enrichment Map
  24. 24. Translational Genomics Research Institute | www.tgen.org GSEA Visualization with Enrichment Map (2010) PLoS ONE, 5(11), 1–12. doi:10.1371/journal.pone.0013984.t001 http://www.baderlab.org/Software/EnrichmentMap Cytoscape App
  25. 25. Translational Genomics Research Institute | www.tgen.org EDDY computes the discrepancy between probability distributions of candidate networks structures based on likelihood of each network across classes of samples.
  26. 26. Translational Genomics Research Institute | www.tgen.org Methodology that can exploit complex interactions between two conditions, such as tumor v normal that might be missed in traditional approaches based on differential gene expression
  27. 27. Translational Genomics Research Institute | www.tgen.org Investigate differential dependencies between conditions –  Evaluation of Differential DependencY –  Computes the differential dependency statistics (JS) and its statistical significance (p-value, via permutation) between conditions, based on the likelihoods of genetic networks (a probabilistic distribution) Likelihood … Possible (or probable) dependency structures JS A B C Gene set of interest A B C A B C Class 1 Class 2 MSigDB, … Gene set DB Class 2 specific dependency Class 1 specific dependency Common dependency EDDY computes the discrepancy between probability distributions of candidate networks structures based on likelihood of each network across classes of samples.
  28. 28. Translational Genomics Research Institute | www.tgen.org Likelihood … Possible (or probable) dependency structures A B C A B C Class 1 Class 2 A B C A B C A B C Class 1 Specific dependency Class 2 Specific Dependency A B C Common dependency
  29. 29. Translational Genomics Research Institute | www.tgen.org •  GSEA appears under-powered, and also select disproportionate amount. •  GSCA appears to be overly sensitive – high false positive (#): Overlap with EDDY gene sets The number of identified subtype-specific gene sets methods GSEA and ts the area C curves in simulation es superior his is partly rom models Comparison of EDDY with other methods in application to TCGA GBM gene expression data Table 2 lists the number of statistically significant gene sets identified with the three different methods for each subtype. EDDY and GSEA produced different results, as EDDY identified 10 $ 22 gene sets for each subtype, whereas GSEA identified 245 gene sets for mesenchymal but just a few for other subtypes. Moreover, there is only and EDDY in identifying differential gene sets from the interaction-focused simulation and EDDY v ¼ 30 0.5965 0.6075 0.6704 0.7064 Table 2. The number of statistically significant gene sets for each subtype Method Classical Mesenchymal Neural Proneural EDDY 13 10 22 22 GSEA 1 (0) 245 (1) 6 (0) 3 (0) GSCA 1590 (11) 1432 (7) 1681 (21) 1563 (17) The number of common cases with EDDY is indicated in the parentheses. byguestonFebruary6,2014http://nar.oxfordjournals.org/Downloadedfrom
  30. 30. Translational Genomics Research Institute | www.tgen.org G2 pathway and p53 pathway gene sets to have differential dependencies that are related to the enrichment of p53 mutations in the proneural subtype. Heat maps show that genes in pathway are not differentially expressed so would not be identified by GSEA technique. Two Pathways Identified with EDDY Enriched in Proneural Glioblastoma Phenotype
  31. 31. Translational Genomics Research Institute | www.tgen.org PARADIGM March 20, 2014 Vol507 Nature MEMo https://www.genome.gov/Multimedia/Slides/TCGA1/TCGA1_Ciriello.pdf Both methods employ multiple genomic data types to identified altered pathways Employed in TCGA studies
  32. 32. Translational Genomics Research Institute | www.tgen.org Personalized Medicine ‘Interpretation Bottleneck’ Drug Target Annotation
  33. 33. Translational Genomics Research Institute | www.tgen.org Personalized Medicine Pipeline Good, B. M., Ainscough, B. J., McMichael, J. F., Su, A. I., & Griffith, O. L. (2014). Organizing knowledge to enable personalization of medicine in cancer, 1–9. doi:10.1186/s13059-014-0438-7
  34. 34. Translational Genomics Research Institute | www.tgen.org Drug Target Matching for Personalized Medicine Good, B. M., Ainscough, B. J., McMichael, J. F., Su, A. I., & Griffith, O. L. (2014). Organizing knowledge to enable personalization of medicine in cancer, 1–9. doi:10.1186/s13059-014-0438-7
  35. 35. Translational Genomics Research Institute | www.tgen.org Framework for Clinical Mapping Genomic Aberration to Drugs Good, B. M., Ainscough, B. J., McMichael, J. F., Su, A. I., & Griffith, O. L. (2014). Organizing knowledge to enable personalization of medicine in cancer, 1–9. doi:10.1186/s13059-014-0438-7
  36. 36. Translational Genomics Research Institute | www.tgen.org Drug Target Resources A number of resources available for drug mapping to gene targets. Issues with available sources •Different annotations schemes and data structures leads to misleading results for end user. •Contextual information around the drug and target is often not annotated. •Not all annotations are therapeutically actionable or appropriate.
  37. 37. Translational Genomics Research Institute | www.tgen.org Drug to Target Annotation Information for linking drugs to genes should be based on primary literature. Curated information should be annotated with controlled vocabulary and arrayed in a structured format. Rules need to capture explicit drug-target response information but also be flexible enough to capture inferred information that may not always be explicitly stated. Important for further research.
  38. 38. Translational Genomics Research Institute | www.tgen.org Example annotation workflow for capturing drug to target information.
  39. 39. Translational Genomics Research Institute | www.tgen.org Visualization of Drug Target Network
  40. 40. Translational Genomics Research Institute | www.tgen.org CNV OtherEXPDRUG SNV Aberration Type Color Key =no_direct =no_inferred=yes_inferred =yes_direct Edge Interaction Key Aberration Type Color Key =DRUG =BIOMARKER =MODIFIER Patient Specific Drug Target Network Patient Genomic Information
  41. 41. Translational Genomics Research Institute | www.tgen.org Impact Areas for Text Mining •Identify and extract interaction information for network and pathway reconstruction. •Aid in identifying and extracting genomic events linked to drug response to better enable personalized medicine.

×