The slides of the talk of @PhilippBayer and I gave on the 28th Chaos Communication Congress. Sources can be found here: https://github.com/drsnuggles/opensnp28c3
A lecture for UW EPI 519 providing background for genome-wide association studies, a few examples of recent papers in the CVD GWAS literature, and some lessons and new directions. The talk was originally given in 2008 (in collaboration with a colleagure), this version has been updated slightly for 2010 and includes references for further reading.
Some of the typefaces may have been mangled on conversion; the file download should be more reliable.
A lecture for UW EPI 519 providing background for genome-wide association studies, a few examples of recent papers in the CVD GWAS literature, and some lessons and new directions. The talk was originally given in 2008 (in collaboration with a colleagure), this version has been updated slightly for 2010 and includes references for further reading.
Some of the typefaces may have been mangled on conversion; the file download should be more reliable.
Join Dr. Dan Sullivan for a fascinating look into the world of clinical research. In this video, you’ll learn the magnitude and complexities of the national and international clinical research community, the drivers of adverse outcomes related to clinical research and the types of resulting litigation, and suggestions for improving patient and practitioner safety in the clinical research process.
Genome sharing projects around the world nijmegen oct 29 - 2015Fiona Nielsen
Genome sharing projects across the world
Did you ever wonder what happened to the exponential increase in genome sequencing data? It is out there around the world and a lot of it is consented for research use. This means that if you just know where to find the data, you can potentially analyse gigabytes of data to power your research.
In this talk Fiona will present community genome initiatives, the genome sharing projects across the world, how you can benefit from this wealth of data in your work, and how you can boost your academic career by sharing and collaboration.
by Fiona Nielsen, Founder and CEO of DNAdigest and Repositive
With a background in software development Fiona pursued her career in bioinformatics research at Radboud University Nijmegen. Now a scientist-turned-entrepreneur Fiona founded DNAdigest and its social enterprise spin-out Repositive Ltd. Both the charity and company focus on efficient and ethical sharing of genetics data for research to accelerate diagnostics and cures for genetic diseases.
Possible Solution for Managing the Worlds Personal Genetic Data - DNA Guide, ...DNA Compass
World DNA Day and Genome Day, Dalian China 2011
"Possible Solution for Managing the Worlds Genetic Data" given by Alice Rathjen, Founder & President DNA Guide, Inc.
Proposes genetic tests be given a rating for quality of science, medical utility and viewing risk so as to facilitate the flow of genetic information in a responsible manner from the lab to the physician and patient. Explains how technology combined with public policy could enable both privacy and personalized medicine to thrive. Advocates individual ownership over personal genetic data and suggests the genome as a data format could provide the foundation for digital human rights.
tags: DNA, genetic testing, privacy, personalized medicine, FDA regulation
Methodologies for Addressing Privacy and Social Issues in Health Data: A Case...Trilateral Research
Huge quantities of complex and diverse data are generated everyday in healthcare institutions, including clinical documentation (diagnostics, lab data, imaging data, etc.), administrative data, activities and cost data, and R&D data from clinical trials.
New Ways for Predictive Analytics and Machine Learning to Advance Population ...Edifecs Inc
The team at University of Washington’s Center for Data Science and Edifecs have collaboratively built predictive tools that use machine-learning to identify patterns in morbidity progress and health status.
Learning Objectives
Hear how other industries are using the latest in predictive analytics and how this experience can be applied to healthcare
Discuss why healthcare needs machine learning and how it compares to traditional analytics
Explore the Data Tsunami and what the future holds for our industry
Precision Medicine Knowledge Graph with GRAKN.AIVaticle
The success or failure of any modern organisation relies greatly on the way they leverage their data. However, most institutions and organisations have no way to aggregate the magnitude and complexity of their disparate data catalogs. They require a unified representation of their data which represents their specific domain truthfully as well as conceptually. In this talk, we introduce how using a knowledge graph addresses these problems in the field of Precision Medicine.
Precision medicine aims at establishing personalised context-centred therapies and diagnostics. This is done by integrating complex and disparate data repositories relating to environmental and molecular origins of diseases.
It has become increasingly difficult to design models for complex diseases which accommodate genetic individual variabilities. We need efficient and successful techniques to integrate, manage, maintain and visualise sizeable datasets. These datasets can be from a multitude of sources, having many various formats and levels of confidentiality. This forms the need to accumulate all this knowledge in one single structured architecture - a knowledge graph.
In this talk, we aspire to inspire a strategy, motivated by translational bioinformatics, to demonstrate how to fulfil the promises of Precision Medicine using Grakn.
This is a clip from the Grakn London Meetup in February 2019. Join the community: www.grakn.ai/community
The slides that will accompany my live webcast for OpenCon 2014 attendees, all about open data in research. The benefits, the how to (both legally & technically), examples, pitfalls, and the future of open research data.
Clinical Research Informatics World 2015Jaime Hodges
Complementing their exceptional series of informatics programming in Boston this spring, Cambridge Healthtech Institute and Clinical Informatics News are proud to launch Clinical Research Informatics World. The event brings together industry leaders, innovative thinkers and decision makers in the areas of clinical operations, clinical trial management, clinical innovation, data analysis, clinical trial informatics, data management, clinical research IT, and clinical information systems for two days of dynamic discussions, expert-led presentations and invaluable networking.
The 2015 program featuring a plenary keynote session and two concurrent conference tracks provides coverage on such topics as big data use and analytics for advancing clinical research, data visualization and analysis trends, new technologies in use for clinical trials (including mobile technology, wearables and social media), and cross-industry data sharing. Learn more at http://www.clinicalinformaticsworld.com
Data Visualization in Biomedical Sciences: More than Meets the EyeNils Gehlenborg
In science, data visualization serves two primary purposes. The first is to explore data sets interactively and the second is to communicate discoveries. However, the requirements for visualizations employed in these activities are very different. Therefore, the software tools used for these purposes are typically disconnected, creating significant challenges for reproducibility and effective communication of discoveries in data-driven biomedical science. In this presentation, I will address how a new approach to creating data visualization tools can connect data analysts and other stakeholders inside and outside the scientific community. I will introduce and demonstrate the "Vistories" approach that was motivated by these question.
Presented at the 5th Cancer Research UK Big Data Analytics Conference on Data Visualization.
Join Dr. Dan Sullivan for a fascinating look into the world of clinical research. In this video, you’ll learn the magnitude and complexities of the national and international clinical research community, the drivers of adverse outcomes related to clinical research and the types of resulting litigation, and suggestions for improving patient and practitioner safety in the clinical research process.
Genome sharing projects around the world nijmegen oct 29 - 2015Fiona Nielsen
Genome sharing projects across the world
Did you ever wonder what happened to the exponential increase in genome sequencing data? It is out there around the world and a lot of it is consented for research use. This means that if you just know where to find the data, you can potentially analyse gigabytes of data to power your research.
In this talk Fiona will present community genome initiatives, the genome sharing projects across the world, how you can benefit from this wealth of data in your work, and how you can boost your academic career by sharing and collaboration.
by Fiona Nielsen, Founder and CEO of DNAdigest and Repositive
With a background in software development Fiona pursued her career in bioinformatics research at Radboud University Nijmegen. Now a scientist-turned-entrepreneur Fiona founded DNAdigest and its social enterprise spin-out Repositive Ltd. Both the charity and company focus on efficient and ethical sharing of genetics data for research to accelerate diagnostics and cures for genetic diseases.
Possible Solution for Managing the Worlds Personal Genetic Data - DNA Guide, ...DNA Compass
World DNA Day and Genome Day, Dalian China 2011
"Possible Solution for Managing the Worlds Genetic Data" given by Alice Rathjen, Founder & President DNA Guide, Inc.
Proposes genetic tests be given a rating for quality of science, medical utility and viewing risk so as to facilitate the flow of genetic information in a responsible manner from the lab to the physician and patient. Explains how technology combined with public policy could enable both privacy and personalized medicine to thrive. Advocates individual ownership over personal genetic data and suggests the genome as a data format could provide the foundation for digital human rights.
tags: DNA, genetic testing, privacy, personalized medicine, FDA regulation
Methodologies for Addressing Privacy and Social Issues in Health Data: A Case...Trilateral Research
Huge quantities of complex and diverse data are generated everyday in healthcare institutions, including clinical documentation (diagnostics, lab data, imaging data, etc.), administrative data, activities and cost data, and R&D data from clinical trials.
New Ways for Predictive Analytics and Machine Learning to Advance Population ...Edifecs Inc
The team at University of Washington’s Center for Data Science and Edifecs have collaboratively built predictive tools that use machine-learning to identify patterns in morbidity progress and health status.
Learning Objectives
Hear how other industries are using the latest in predictive analytics and how this experience can be applied to healthcare
Discuss why healthcare needs machine learning and how it compares to traditional analytics
Explore the Data Tsunami and what the future holds for our industry
Precision Medicine Knowledge Graph with GRAKN.AIVaticle
The success or failure of any modern organisation relies greatly on the way they leverage their data. However, most institutions and organisations have no way to aggregate the magnitude and complexity of their disparate data catalogs. They require a unified representation of their data which represents their specific domain truthfully as well as conceptually. In this talk, we introduce how using a knowledge graph addresses these problems in the field of Precision Medicine.
Precision medicine aims at establishing personalised context-centred therapies and diagnostics. This is done by integrating complex and disparate data repositories relating to environmental and molecular origins of diseases.
It has become increasingly difficult to design models for complex diseases which accommodate genetic individual variabilities. We need efficient and successful techniques to integrate, manage, maintain and visualise sizeable datasets. These datasets can be from a multitude of sources, having many various formats and levels of confidentiality. This forms the need to accumulate all this knowledge in one single structured architecture - a knowledge graph.
In this talk, we aspire to inspire a strategy, motivated by translational bioinformatics, to demonstrate how to fulfil the promises of Precision Medicine using Grakn.
This is a clip from the Grakn London Meetup in February 2019. Join the community: www.grakn.ai/community
The slides that will accompany my live webcast for OpenCon 2014 attendees, all about open data in research. The benefits, the how to (both legally & technically), examples, pitfalls, and the future of open research data.
Clinical Research Informatics World 2015Jaime Hodges
Complementing their exceptional series of informatics programming in Boston this spring, Cambridge Healthtech Institute and Clinical Informatics News are proud to launch Clinical Research Informatics World. The event brings together industry leaders, innovative thinkers and decision makers in the areas of clinical operations, clinical trial management, clinical innovation, data analysis, clinical trial informatics, data management, clinical research IT, and clinical information systems for two days of dynamic discussions, expert-led presentations and invaluable networking.
The 2015 program featuring a plenary keynote session and two concurrent conference tracks provides coverage on such topics as big data use and analytics for advancing clinical research, data visualization and analysis trends, new technologies in use for clinical trials (including mobile technology, wearables and social media), and cross-industry data sharing. Learn more at http://www.clinicalinformaticsworld.com
Data Visualization in Biomedical Sciences: More than Meets the EyeNils Gehlenborg
In science, data visualization serves two primary purposes. The first is to explore data sets interactively and the second is to communicate discoveries. However, the requirements for visualizations employed in these activities are very different. Therefore, the software tools used for these purposes are typically disconnected, creating significant challenges for reproducibility and effective communication of discoveries in data-driven biomedical science. In this presentation, I will address how a new approach to creating data visualization tools can connect data analysts and other stakeholders inside and outside the scientific community. I will introduce and demonstrate the "Vistories" approach that was motivated by these question.
Presented at the 5th Cancer Research UK Big Data Analytics Conference on Data Visualization.
Slides of the Talk Fabian Zimmer & I gave on the SIGINT 12 in Cologne. A video of the talk can be found here:
http://ftp.ccc.de/events/sigint12/mp4/vortrag_mp6_og_-_2012-05-19_20_00_-_power_to_the_patient_-_bastian_greshake_-_fabian_zimmer_-_40.mp4
The slides i used for the defense of my BSc-Thesis. A blogpost in german about the work can be found here: http://www.wissenslogs.de/wblogs/blog/bierologie/biologie/2010-08-11/meine-bachelor-arbeit-transkriptom-analysen-f-r-jeden
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Crowdsourcing GWAS
1. Introduction Open GWAS Privacy & Implications Discussion
Crowdsourcing Genome Wide Association
Studies
Bastian Greshake and Philipp Bayer
28.12.2011
2. Introduction Open GWAS Privacy & Implications Discussion
Overview
1 Introduction
Association studies?
2 Open GWAS
In company vaults
Out of vaults
3 Privacy & Implications
Some Implications
Consequences
4 Discussion
Outlook
3. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
What are GWAS?
Genome-wide Association Studies
4. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
What are GWAS?
Genome-wide Association Studies
Link genetic variants (SNPs) to certain traits like eye or
hair colour or to diseases like Diabetes, types of cancer
5. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Single Nucleotide Polymorphism
Source: http://en.wikipedia.org/wiki/File:Dna-SNP.svg
6. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
How to analyse SNPs?
Source: http://en.wikipedia.org/wiki/File:NA hybrid.svg
7. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
How do GWAS work?
8. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
How do GWAS work?
9. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
How do GWAS work?
10. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
How do GWAS work?
11. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Some GWAS-examples
Sladek et al. (2007) identified four gene locations linked
to heightened type 2 diabetes risk
12. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Some GWAS-examples
Sladek et al. (2007) identified four gene locations linked
to heightened type 2 diabetes risk
Kogan et al. (2011) linked rs53576 (G:G) to pro-social
behaviour
13. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Some GWAS-examples
Sladek et al. (2007) identified four gene locations linked
to heightened type 2 diabetes risk
Kogan et al. (2011) linked rs53576 (G:G) to pro-social
behaviour
The Wellcome Trust Case Control Consortium (2007)
linked 24 locations to 7 major diseases
14. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Problems with GWAS
Large enough sample size
15. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Problems with GWAS
Large enough sample size
Correcting for multiple testing
16. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Problems with GWAS
Large enough sample size
Correcting for multiple testing
Correlation != Causation
17. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Putting GWAS to use
Direct-To-Consumer genetic testing
Analyse about 1 million SNPs and provide summary of
disease risks & ancestry
About $200 for a genotyping
18. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Putting GWAS to use
Direct-To-Consumer genetic testing
Analyse about 1 million SNPs and provide summary of
disease risks & ancestry
About $200 for a genotyping
Providers: 23andMe, deCODEme, FamilyTree DNA, ...
19. Introduction Open GWAS Privacy & Implications Discussion
Association studies?
Putting GWAS to use
Direct-To-Consumer genetic testing
Analyse about 1 million SNPs and provide summary of
disease risks & ancestry
About $200 for a genotyping
Providers: 23andMe, deCODEme, FamilyTree DNA, ...
You get access to the raw data!
20. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Numbers on DTC
23andMe alone has over 100.000 customers
21. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Numbers on DTC
23andMe alone has over 100.000 customers
76 % of their customers agree to participate in research
22. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Numbers on DTC
23andMe alone has over 100.000 customers
76 % of their customers agree to participate in research
59 % of them share phenotypic information with 23andMe
23. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Research in company labs
23andMe published results of studies with up to 30.000
participants
24. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Research in company labs
23andMe published results of studies with up to 30.000
participants
Replication of older GWAS
25. Introduction Open GWAS Privacy & Implications Discussion
In company vaults
Research in company labs
23andMe published results of studies with up to 30.000
participants
Replication of older GWAS
Finding new associations for Parkinsons disease
26. Introduction Open GWAS Privacy & Implications Discussion
Out of vaults
Data sharing
People are already sharing the raw data of DTC tests
27. Introduction Open GWAS Privacy & Implications Discussion
Out of vaults
Data sharing
People are already sharing the raw data of DTC tests
1-5 % of 23andMe customers would be enough to
perform simple GWAS
28. Introduction Open GWAS Privacy & Implications Discussion
Out of vaults
Data sharing
People are already sharing the raw data of DTC tests
1-5 % of 23andMe customers would be enough to
perform simple GWAS
The Personal Genome Project: Open data, but closed
participation
29. Introduction Open GWAS Privacy & Implications Discussion
Out of vaults
Willing to share?
30. Introduction Open GWAS Privacy & Implications Discussion
Out of vaults
Willing to share?
31. Introduction Open GWAS Privacy & Implications Discussion
Some Implications
What can happen to your open data?
Positive and negative consequences
32. Introduction Open GWAS Privacy & Implications Discussion
Some Implications
What can happen to your open data?
Positive and negative consequences
Possibly extremely bad consequences
33. Introduction Open GWAS Privacy & Implications Discussion
Some Implications
What can happen to your open data?
Positive and negative consequences
Possibly extremely bad consequences
Up to you to decide whether you want to open your data
34. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Positive consequences
More knowledge about yourself
35. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Positive consequences
More knowledge about yourself
Cheap, open science
36. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Positive consequences
More knowledge about yourself
Cheap, open science
Great data-source for citizen scientists
37. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Negative consequences
People know more about you than you might like
38. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Negative consequences
People know more about you than you might like
Including your boss, insurance company, government...
39. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Negative consequences
People know more about you than you might like
Including your boss, insurance company, government...
Knowledge isn’t static: Future research could show new,
negative (or positive) associations.
40. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Negative consequences
People know more about you than you might like
Including your boss, insurance company, government...
Knowledge isn’t static: Future research could show new,
negative (or positive) associations.
Personal SNPs very similar to parents and relatives
41. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Somebody Else’s Problem? A case study
42. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Somebody Else’s Problem? A case study
43. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Somebody Else’s Problem? A case study
44. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Possible Solutions
What about laws?
45. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Possible Solutions
What about laws?
US: Genetic Information Nondiscrimination Act (GINA,
2008)
46. Introduction Open GWAS Privacy & Implications Discussion
Consequences
Possible Solutions
What about laws?
US: Genetic Information Nondiscrimination Act (GINA,
2008)
Germany: Gendiagnostikgesetz (GenDG, 2010)
47. Introduction Open GWAS Privacy & Implications Discussion
For those who still want to share: Open GWAS
48. Introduction Open GWAS Privacy & Implications Discussion
openSNP
No central repository for open genotypings!
49. Introduction Open GWAS Privacy & Implications Discussion
openSNP
No central repository for open genotypings!
We’ve created openSNP.org
50. Introduction Open GWAS Privacy & Implications Discussion
openSNP
No central repository for open genotypings!
We’ve created openSNP.org
open source repository for CC0-genotypings from
23andme, deCODEme and others
51. Introduction Open GWAS Privacy & Implications Discussion
... continued
Allows users to annotate with phenotypes (hair colour,
nicotine dependence, SAT-scores...)
52. Introduction Open GWAS Privacy & Implications Discussion
... continued
Allows users to annotate with phenotypes (hair colour,
nicotine dependence, SAT-scores...)
Everybody can download everything
53. Introduction Open GWAS Privacy & Implications Discussion
... continued
Allows users to annotate with phenotypes (hair colour,
nicotine dependence, SAT-scores...)
Everybody can download everything
So far: 81 genotypings and 207 users
54. Introduction Open GWAS Privacy & Implications Discussion
Conclusions
Open GWAS are the future of personalised medicine
55. Introduction Open GWAS Privacy & Implications Discussion
Conclusions
Open GWAS are the future of personalised medicine
It’s in the hands of users to make or break the situation
56. Introduction Open GWAS Privacy & Implications Discussion
Conclusions
Open GWAS are the future of personalised medicine
It’s in the hands of users to make or break the situation
Chance to take science into our own hands
57. Introduction Open GWAS Privacy & Implications Discussion
Outlook
Future of openSNP
We’ve won the PLoS/Mendeley Binary Battle
58. Introduction Open GWAS Privacy & Implications Discussion
Outlook
Future of openSNP
We’ve won the PLoS/Mendeley Binary Battle
Got some funding to get more people (who are willing to
share) genotyped (around 5000EUR)
59. Introduction Open GWAS Privacy & Implications Discussion
Outlook
Future of openSNP
We’ve won the PLoS/Mendeley Binary Battle
Got some funding to get more people (who are willing to
share) genotyped (around 5000EUR)
Details on this will be released at the start of the next
year
60. Introduction Open GWAS Privacy & Implications Discussion
Outlook
Future of openSNP
We’ve won the PLoS/Mendeley Binary Battle
Got some funding to get more people (who are willing to
share) genotyped (around 5000EUR)
Details on this will be released at the start of the next
year
Constantly improving the project (and are happy if
somebody wants to help)
61. Introduction Open GWAS Privacy & Implications Discussion
Outlook
The end
Thanks for listening. Any questions?
For further questions: @gedankenstuecke
or @PhilippBayer
62. Introduction Open GWAS Privacy & Implications Discussion
Outlook
References
Do et al. (2011) Web-Based Genome-Wide Association Study Identifies Two Novel Loci and a Substantial Genetic
Component for Parkinson’s Disease. PLoS Genetics 7(6): e1002141. doi:10.1371/journal.pgen.1002141
Eriksson et al. (2010) Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits.
PLoS Genet 6(6): e1000993. doi:10.1371/journal.pgen.1000993
Kogan, et al. (2011): Thin-slicing study of the oxytocin receptor (OXTR) gene and the evaluation and expression
of the prosocial disposition. Proceedings of the National Academy of Sciences
Sladek et al. (2007): A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445
(7130): 881-5.
The Wellcome Trust Case Control Consortium (2007): Genome-wide association study of 14,000 cases of seven
common diseases and 3,000 shared controls. Nature 447: 661-678.