pattern recognition in clinical data

Download Pattern Recognition in clinical data

Post on 10-May-2015

174 views

Category:

Education

2 download

Embed Size (px)

TRANSCRIPT

  • 1.I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYPattern Recognition In Clinical Data Saket Choudhary Dual Degree Project Guide: Prof. Santosh NoronhaC G C A T C G A G C T C G C G T C G A G C TOctober 30, 2013C ONCLUSIONS

2. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYI NTRODUCTION I NTRODUCTION Objective S IGNIFICANT M UTATIONS Next Generation Sequencing Motivation Computational Methods for Driver Detection V IRAL G ENOME D ETECION Workow R EPRODUCIBILITY Reproducibility C ONCLUSIONS Wrapping upC ONCLUSIONS 3. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 4. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 5. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 6. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 7. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 8. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 9. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 10. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 11. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 12. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 13. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 14. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 15. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSO BJECTIVE BWA v/s BWAPSSMGalaxy WorkowViral Genome IntegrationBenchmarking Alignment toolsTools for Biologists Reproducible analysis Driver & Passenger Mutation DetectionGalaxy ToolsBetter/New AlgorithmsNext Generation Sequencing & Cancer ResearchDriver & Passenger Mutation DetectionLit. SurveyEnsembl Method 16. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYN EXT G ENERATION S EQUENCINGC G C G T C G A G C T A G C AC ONCLUSIONS 17. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYN EXT G ENERATION S EQUENCINGC G C G T C G A G C T A G C AC ONCLUSIONS 18. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYN EXT G ENERATION S EQUENCINGC G C G T C G A G C T A G C AG C G TC G A GC T A GC ONCLUSIONS 19. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYN EXT G ENERATION S EQUENCING C G C G T C G A G C T A G C AG C G TC G A GC T A GA G C G C G T C G A G C T A G C A C AC ONCLUSIONS 20. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HY ?Molecular Approach: Study of variations at the base level Low Cost: 1000$ genome Faster: Quicker than traditional sequencing techniquesC ONCLUSIONS 21. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HY ?Molecular Approach: Study of variations at the base level Low Cost: 1000$ genome Faster: Quicker than traditional sequencing techniquesC ONCLUSIONS 22. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HY ?Molecular Approach: Study of variations at the base level Low Cost: 1000$ genome Faster: Quicker than traditional sequencing techniquesC ONCLUSIONS 23. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HERE ?Study variations, genotype-phenotype association Look for markers of diseases PrognosisC ONCLUSIONS 24. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HERE ?Study variations, genotype-phenotype association Look for markers of diseases PrognosisC ONCLUSIONS 25. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYNGS: W HERE ?Study variations, genotype-phenotype association Look for markers of diseases PrognosisC ONCLUSIONS 26. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSNGS: M UTATIONS3x109 base pairs We are all 99.9% similar, at DNA level More than 2 million SNPs No particular pattern of SNPs If a certain mutation causes a change in an amino acid, it is referred to as non synonymous(nsSNV) 27. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYD RIVERS AND PASSENGERS I Cancer is known to arise due to mutations Not all mutations are equally important!Somatic Mutations Set of mutations acquired after zygote formation, over and above the germline mutationsDriver Mutations Mutations that confer growth advantages to the cell, being selected positively in the tumor tissueC ONCLUSIONS 28. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSD RIVERS AND PASSENGERSDrivers are NOT simply loss of function mutations, but more than that: Loss of function: Inactivate tumor suppressor proteins Gain of function: Activates normal genes transforming them to oncogenes Drug Resistance Mutations: Mutations that have evolved to overcome the inhibitory effect of drugs 29. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSD RIVERS AND PASSENGERSDrivers are NOT simply loss of function mutations, but more than that: Loss of function: Inactivate tumor suppressor proteins Gain of function: Activates normal genes transforming them to oncogenes Drug Resistance Mutations: Mutations that have evolved to overcome the inhibitory effect of drugs 30. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECIONR EPRODUCIBILITYC ONCLUSIONSD RIVERS AND PASSENGERSDrivers are NOT simply loss of function mutations, but more than that: Loss of function: Inactivate tumor suppressor proteins Gain of function: Activates normal genes transforming them to oncogenes Drug Resistance Mutations: Mutations that have evolved to overcome the inhibitory effect of drugs 31. I NTRODUCTIONS IGNIFICANT M UTATIONSV IRAL G ENOME D ETECION