Practical Guide to the $1000 Genome (2014)
Transcript of Practical Guide to the $1000 Genome (2014)
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A Practical Guide to the $1000 Genome
Michael Heltzen, CEO & Co-Founder
Shawn C. Baker, Ph.D., CSO & Co-Founder
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The Sequencing Marketplace
Match researchers with sequencing providers
Neutral stance
Unique perspective
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Where to start?
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How do I communicate it?
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Pick 2, but not all 3…
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The lab’s side of the problem
Overcapacity…
What is our value proposition?
What is an optimal customer for us?
Buyers don’t know what they want?
How do I price?
Should I generalize or specialize?
Technologies and needs change all the time…
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Lack of standards
Why are standards so hard for us as an industry?
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How does AllSeq work?
AllSeq connect researcher with NGS sequencing needs, to the most optimal lab for each case
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It works like this
Project design& QA
Offers & Picking a lab
Match & talks
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Human and
diseases
Virus and
Bacteria
Plants and
Animals
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Over to Shawn and the $1000 Genome
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The $1000 genome is here!
(sort of…)
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The HiSeq X Ten: What is it?
Data output:
– 600 Gb/day
– 1.8 Tb/run
– ~5 whole human genomes/day
– 1800 genomes per year
Patterned flow cells
Improved optics
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What’s the catch?
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$1000 Genome
=$800 – sequencing$135 – amortization$65 – library prep
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$1000 Genome
= $1M
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$1000 Genome
= $10M
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1 day = $5000
=
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1 year = $1,800,000
=
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1 year= $18,000,000
=
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4 years = $72,000,000
=
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Allseq.com/1000-genome
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…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
Whole Genome vs Exome
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Whole Genome
~2.8Gb = ~ 95% coverage
…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
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Exome Sequencing
~40Mb = ~ 1.3% coverage
…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
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Whole Genome vs Exome
WGS Exome
Price ✓Coverage ✓
Uniformity ✓Analysis ✓
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HiSeq X Ten Dataset
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HiSeq X Ten Dataset
NA12878D and NA12878J – Coriell Cell Repository
Illumina TruSeq Nano, 2X150bp, 350bp insert
>120Gb, 87% >Q30
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Analyzing the Data
Primary
• Base calling
• QC
Secondary
• Assembly
• Alignment
Tertiary
• Annotations
• Visualization
• Statistics
Reporting
• Research
• Clinical
IT Infrastructure/Data Management
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Analyzing the Data
Primary
• Base calling
• QC
Secondary
• Assembly
• Alignment
Tertiary
• Annotations
• Visualization
• Statistics
Reporting
• Research
• Clinical
IT Infrastructure/Data Management
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Analyzing the Data
@EAS54_6_R1_2_1_413_324CCCTTCTTGTCTTCAGCGTTTCTCC+;;3;;;;;;;;;;;;7;;;;;;;88@EAS54_6_R1_2_1_540_792TTGGCAGGCCAAGGCCGATGGATCA+;;;;;;;;;;;7;;;;;-;;;3;83@EAS54_6_R1_2_1_443_348GTTGCTTCTGGCGTGGGTGGGGGGG+EAS54_6_R1_2_1_443_348;;;;;;;;;;;9;7;;.7;393333
fastq file:
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Data Analysis & Interpretation
Medical report:
Example from knomeDISCOVERY
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Analyzing the Data
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Long Reads: PacBio
~2kb ~10kb
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Long Reads: Moleculo
Moleculo TruSeq Synthetic Long Reads
10kb ‘synthetic’ reads
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Long Reads: Oxford Nanopore
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Single Cell/Cell-Free DNA Sequencing
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Moving Beyond the Genome
Credits: Darryl Leja (NHGRI), Ian Dunham (EBI)
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Topic: Researchers vs. clinical.
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Trends: Transition to the Clinic
Increased output
Lower cost
Rapid updates
Ease of use
Quick TAT
Stability
Researchers Clinicians
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Approval trend: Transition to the Clinic
MiSeq Dx
– FDA clearance Nov 2013
– Will also submit 2500 and NIPT assay
PGM
– Listed with FDA Sept 2014
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Opportunities and challenges
What is great– We are getting there…– It is going faster and better/cheaper/faster– More and more people are starting to understand
What is not so great– We are not there yet – We are not even as far as many people think we are– Lack of standards (especially for the clinical market)
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First: The bad part
Technical error sources:
– Sampling
– Sequencing
– Bioinformatics
– Interpretation
Lack of standards…
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Then: The good part
Large steps in the right direction on all fronts. Is it only a matter of time now…
The new genomics technologies are slowly getting ripe for the clinic!
We are collectively making the world a better place!
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www.allseq.com@[email protected]