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A Practical Guide to the $1000
Genome
Michael Heltzen, CEO & Co-Founder
Shawn C. Baker, Ph.D., CSO & Co-Founder
The Sequencing Marketplace
Match researchers with sequencing providers
Neutral stance
Unique perspective
Where to start?
How do I communicate it?
Pick 2, but not all 3…
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…
Lack of standards
Why are standards so hard for us as an industry?
How does AllSeq work?
AllSeq connect researcher
with NGS sequencing
needs, to the most optimal
lab for each case
It works like this
Project design
& QA
Offers &
Picking a lab
Match
& talks
Human
and
diseases
Virus
and
Bacteria
Plants
and
Animals
Over to Shawn and the $1000 Genome
The $1000 genome is here!
(sort of…)
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
What’s the catch?
$1000 Genome
=
$800 – sequencing
$135 – amortization
$65 – library prep
$1000 Genome
= $1M
$1000 Genome
= $10M
1 day = $5000
=
1 year = $1,800,000
=
1 year= $18,000,000
=
4 years = $72,000,000
=
Allseq.com/1000-genome
…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
Whole Genome vs Exome
Whole Genome
~2.8Gb = ~ 95% coverage
…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
Exome Sequencing
~40Mb = ~ 1.3% coverage
…ACCATGATCTAGCCGATTTCGA…
…TGGTACTAGATCGGCTAAAGCT…
Whole Genome vs Exome
WGS Exome
Price ✓
Coverage ✓
Uniformity ✓
Analysis ✓
HiSeq X Ten Dataset
HiSeq X Ten Dataset
NA12878D and NA12878J – Coriell Cell
Repository
Illumina TruSeq Nano, 2X150bp, 350bp insert
>120Gb, 87% >Q30
Analyzing the Data
Primary
• Base calling
• QC
Secondary
• Assembly
• Alignment
Tertiary
• Annotations
• Visualization
• Statistics
Reporting
• Research
• Clinical
IT Infrastructure/Data Management
Analyzing the Data
Primary
• Base calling
• QC
Secondary
• Assembly
• Alignment
Tertiary
• Annotations
• Visualization
• Statistics
Reporting
• Research
• Clinical
IT Infrastructure/Data Management
Analyzing the Data
@EAS54_6_R1_2_1_413_324
CCCTTCTTGTCTTCAGCGTTTCTCC
+
;;3;;;;;;;;;;;;7;;;;;;;88
@EAS54_6_R1_2_1_540_792
TTGGCAGGCCAAGGCCGATGGATCA
+
;;;;;;;;;;;7;;;;;-;;;3;83
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+EAS54_6_R1_2_1_443_348
;;;;;;;;;;;9;7;;.7;393333
fastq file:
Data Analysis & Interpretation
Medical report:
Example from knomeDISCOVERY
Analyzing the Data
Long Reads: PacBio
~2kb  ~10kb
Long Reads: Moleculo
Moleculo  TruSeq Synthetic Long Reads
10kb ‘synthetic’ reads
Long Reads: Oxford Nanopore
Single Cell/Cell-Free DNA Sequencing
Moving Beyond the Genome
Credits: Darryl Leja (NHGRI), Ian Dunham (EBI)
Topic: Researchers vs. clinical.
Trends: Transition to the Clinic
Increased output
Lower cost
Rapid updates
Ease of use
Quick TAT
Stability
Researchers Clinicians
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
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)
First: The bad part
Technical error sources:
– Sampling
– Sequencing
– Bioinformatics
– Interpretation
Lack of standards…
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!
www.allseq.com
@allseq
info@allseq.com

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Practical Guide to the $1000 Genome (2014)

Hinweis der Redaktion

  1. 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…
  2. 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…
  3. You can often just pick two of the following: price, turnaround time and quality * Quality is different from buyer to buyer.
  4. 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
  5. 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.
  6. Huge area of development Show overall spectrum of analysis and scope of who covers what Focus on the annotation and reporting
  7. Huge area of development Show overall spectrum of analysis and scope of who covers what Focus on the annotation and reporting
  8. Process discussion with your doctor sample collection sample prep sequencing data analysis data interpretation
  9. 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
  10. Just the beginning Trascriptome, Epigenome, Metagenome
  11. 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….
  12. 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