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Genomics, Bioinformatics, and PathologyDR. DAN GASTON
BEDARD LAB
DEPARTMENT OF PATHOLOGY
DALHOUSIE UNIVERSITY
MAY 13TH, 2015
Genomic Pathology
Healthcare
Research
Innovation
Why Genomics?
Why Genomics?
Cost
Knowledge Utility
$398,000 -> $0.40
NGS: Next-Generation Sequencing. A group of different sequencing technologies defined by high throughput and low cost
A Short Primer on Common Terms
NGS: Next-Generation Sequencing. A group of different sequencing technologies defined by high throughput and low cost
Short Read: The output from most NGS sequencing technologies. Range from 30bp to 300bp
A Short Primer on Common Terms
NGS: Next-Generation Sequencing. A group of different sequencing technologies defined by high throughput and low cost
Short Read: The output from most NGS sequencing technologies. Range from 30bp to 300bp
Mapping: Placing sequencing reads on to a reference genome
A Short Primer on Common Terms
NGS: Next-Generation Sequencing. A group of different sequencing technologies defined by high throughput and low cost
Short Read: The output from most NGS sequencing technologies. Range from 30bp to 300bp
Mapping: Placing sequencing reads on to a reference genome
Variant Calling: Identifying sites of genetic variation between a sample and a reference genome
A Short Primer on Common Terms
A Short Primer on Common Terms
NGS: Next-Generation Sequencing. A group of different sequencing technologies defined by high throughput and low cost
Short Read: The output from most NGS sequencing technologies. Range from 30bp to 300bp
Mapping: Placing sequencing reads on to a reference genome
Variant Calling: Identifying sites of genetic variation between a sample and a reference genome
Paired End: Two short reads from the same fragment of the genome, one from each end
The Players
The Players
Next-Gen Sequencing Overview
Next-Gen Sequencing Overview
Illumina Sequencing: The Basics
Targeted Sequencing
Targeted Sequencing
The Data
The Data: FastQ Format
Read ID
Sequence
Quality line
NGS Bioinformatics Workflow
Unpacking the Black Box
Unpacking the Black Box
Quality assurance of primary data
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Identify genetic variation (mutations, translocations, etc)
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Identify genetic variation (mutations, translocations, etc)
Quality assurance of variants
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Identify genetic variation (mutations, translocations, etc)
Quality assurance of variants
Variant annotation
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Identify genetic variation (mutations, translocations, etc)
Quality assurance of variants
Variant annotation
Variant filtering
Unpacking the Black Box
Quality assurance of primary data
Map short reads to a reference
Quality assurance of mapping process
Identify genetic variation (mutations, translocations, etc)
Quality assurance of variants
Variant annotation
Variant filtering
Reporting (Text, Visualization)
Genomic Oncology
Tumour SampleDNA
Non-Tumour Sample
DNA
Databases and Annotations
Sequence
Tumour Specific
Mutations
Tumour Classification
Drugs
Short Read Mapping
Short Read Mapping
AGCTGGGATTTCGGAAAAGTCCGATCCCTTTAAGCGAA
AGCTGGGAT
GATTTCGGAAAA
TCGGAAAAGTC TTTAAGCGAA
TCCCTTTAAGGTCCGATCCC
GAAAAGTCCGATCCTGGGATTTCGG
TTCGGAAAAG CGATCCCTTTAAGCAAAGTCCGATCC
Variant Calling
AGCTGGGATTTCGGAAAAGTCCGATCCCTTTAAGCGAA
AGCTGGGAT
GATTTCGGAAAA
TCGGAAAAGTC TTTAAGCGAA
TCCCTTTAAGGTCCGATCCC
GAAAAGTCCGAGCCTGGGATTTCGG
TTCGGAAAAG CGAGCCCTTTAAGCAAAGTCCGAGCC
Variant Annotation
Variant Databases
Public DatabasesClinical Testing Databases
Pharmaceutical Company Databases
Important Considerations
Timeline to Action
Day 0 Day 30 ?
Timeline to Action
Day 0 Day 14?
Timeline to Action
Day 0 Day 7?
Data Storage
Data Storage: Sequencing Centres
Data Storage: Sequencing Centres
Data Storage: Smaller Sequencing Centres
Data Storage: Smaller Sequencing Centres
Data Storage: Focused Sequencing
Data Storage: Focused Sequencing
Data Storage: Focused Sequencing
Data Sharing
Clinical Bioinformatics
Validate, validate, validate!
Clinical Reporting
Genetic Variant Reporting
Genetic Variant Reporting
Genetic Variant Reporting
Genetic Variant Reporting
Levels of Evidence/Support
Algorithmic Prediction
Levels of Evidence/Support
Algorithmic Prediction+ Gene of Clinical Significance
Algorithmic Prediction
Levels of Evidence/Support
Algorithmic Prediction+ Gene of Clinical Significance
Algorithmic Prediction
Clinical Variant in Other Malignancy
Levels of Evidence/Support
Algorithmic Prediction+ Gene of Clinical Significance
Algorithmic Prediction
Clinical Variant in Other Malignancy
Clinical Variant in Malignancy
Algorithmic Prediction+ Gene of Clinical Significance
Algorithmic Prediction
Variants of Unknown Significance
Incidental Findings ACMG Recommendations
56 Genes
Report on known pathogenic mutations for all
Report on suspected (predicted) pathogenic for some
Based on actionability
Allow for patient opt-out?
The Future
Monitoring For Cancer Chemotherapy Resistance
Field Sequencing and Real-Time Analysis
Takeaways and Key Points
Conclusions
Clinical sequencing is here
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Future proofing
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Future proofing
Be comfortable with genetics
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Future proofing
Be comfortable with genetics
Make friends with your friendly local bioinformatician
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Future proofing
Be comfortable with genetics
Make friends with your friendly local bioinformatician
Leveraging 'Big Data' to make big decisions
Conclusions
Clinical sequencing is here
Bit of a learning curve but pay-off is potentially huge
Future proofing
Be comfortable with genetics
Make friends with your friendly local bioinformatician
Leveraging 'Big Data' to make big decisions
Future: Clinical trails of size 1
Conclusions
Cost
Knowledge Utility
Conclusions
Pathologists
Bioinformaticians Geneticists
