Practical Guide to the $1000 Genome (2014)
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This document discusses the progress toward achieving the $1000 whole human genome and the challenges still remaining. It provides an overview of sequencing technologies like the HiSeq X Ten that can sequence a genome for around $1000 but requires large upfront investment. While costs are decreasing and technologies improving, lack of standards still pose issues for clinical adoption. However, trends toward more output, lower costs, and easier use point to genomics gradually becoming established in healthcare.
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Practical Guide to the $1000 Genome (2014)
- 1. A Practical Guide to the $1000 Genome Michael Heltzen, CEO & Co-Founder Shawn C. Baker, Ph.D., CSO & Co-Founder
- 2. The Sequencing Marketplace Match researchers with sequencing providers Neutral stance Unique perspective
- 4. How do I communicate it?
- 5. Pick 2, but not all 3…
- 6. 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…
- 7. Lack of standards Why are standards so hard for us as an industry?
- 8. How does AllSeq work? AllSeq connect researcher with NGS sequencing needs, to the most optimal lab for each case
- 9. It works like this Project design & QA Offers & Picking a lab Match & talks
- 11. Over to Shawn and the $1000 Genome
- 12. The $1000 genome is here! (sort of…)
- 13. 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
- 16. $1000 Genome = $800 – sequencing $135 – amortization $65 – library prep
- 19. 1 day = $5000 =
- 20. 1 year = $1,800,000 =
- 22. 4 years = $72,000,000 =
- 25. Whole Genome ~2.8Gb = ~ 95% coverage …ACCATGATCTAGCCGATTTCGA… …TGGTACTAGATCGGCTAAAGCT…
- 26. Exome Sequencing ~40Mb = ~ 1.3% coverage …ACCATGATCTAGCCGATTTCGA… …TGGTACTAGATCGGCTAAAGCT…
- 27. Whole Genome vs Exome WGS Exome Price ✓ Coverage ✓ Uniformity ✓ Analysis ✓
- 28. HiSeq X Ten Dataset
- 29. HiSeq X Ten Dataset NA12878D and NA12878J – Coriell Cell Repository Illumina TruSeq Nano, 2X150bp, 350bp insert >120Gb, 87% >Q30
- 30. Analyzing the Data Primary • Base calling • QC Secondary • Assembly • Alignment Tertiary • Annotations • Visualization • Statistics Reporting • Research • Clinical IT Infrastructure/Data Management
- 31. Analyzing the Data Primary • Base calling • QC Secondary • Assembly • Alignment Tertiary • Annotations • Visualization • Statistics Reporting • Research • Clinical IT Infrastructure/Data Management
- 33. Data Analysis & Interpretation Medical report: Example from knomeDISCOVERY
- 35. Long Reads: PacBio ~2kb ~10kb
- 36. Long Reads: Moleculo Moleculo TruSeq Synthetic Long Reads 10kb ‘synthetic’ reads
- 37. Long Reads: Oxford Nanopore
- 38. Single Cell/Cell-Free DNA Sequencing
- 40. Moving Beyond the Genome Credits: Darryl Leja (NHGRI), Ian Dunham (EBI)
- 41. Topic: Researchers vs. clinical.
- 42. Trends: Transition to the Clinic Increased output Lower cost Rapid updates Ease of use Quick TAT Stability Researchers Clinicians
- 43. 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
- 44. 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)
- 45. First: The bad part Technical error sources: – Sampling – Sequencing – Bioinformatics – Interpretation Lack of standards…
- 46. 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!
Notes de l'éditeur
- Often “don’t know where to start”? What is my need? That service provider is the best for me… Even the experienced people get confused…
- How do I communicate it (and the providers different lingo and tech terms). It is not just technical things, but also the practical things… Do I really have to speak to all those people…
- You can often just pick two of the following: price, turnaround time and quality * Quality is different from buyer to buyer.
- Use our online software to make a “Project Design” of your sequencing project Get QA and questions from AllSeq if relevant Get matched with 5-10 of the most optimal labs Get prices and terms + chat/write with them directly
- We see all kinds of projects: Human and disease, plants and animals & virus, fungus and bacteria. This year we have had app. 100 sequencing projects that have been entered on the marketplace.
- Huge area of development Show overall spectrum of analysis and scope of who covers what Focus on the annotation and reporting
- Huge area of development Show overall spectrum of analysis and scope of who covers what Focus on the annotation and reporting
- Process discussion with your doctor sample collection sample prep sequencing data analysis data interpretation
- MAP = 500 labs High error rates (~20-25%), but improving Outputs ~200-500Mb, 1Gb internal runs PromethION = multiple ASICs or flow cells Up to 100k pores Could generate 300-400Gb per day
- Just the beginning Trascriptome, Epigenome, Metagenome
- How are researchers and clinical people different – progress and updates vs. stability and be consistent (due to liability) Why is a researcher work in the hospital not always a clinical case – as it is research Where is the doctor and geneticist in all of this – how is the set up….
- Technical error sources: Sampling: Single cell single molecule Sequencing technologies (application, short reads, different error profiles) Bioinformatics (less than optimal reference genomes and databases) Lack of standards, so people are on the same page when it comes to the errors