Links

Learning Population Genetics

  • PopGen Notes by Graham Coop [link]
  • Lecture Notes on Computational and Mathematical Population Genetics by Yun Song [link]
  • Links on Quantitative Genetics learning resources from Bruce Walsh [link]
  • Mathematical modeling in ecology and evolution by Sally Otto and Troy Day [link]
  • Shiny-based tools for learning pop gen by Silas Tittes [link]
  • learnPopGen web interfaces by Liam Revell [link]

Learning Stochastic Processes and Statistical Inference

  • “fiveMinuteStats” page by Matthew Stephens (and other contributors) [link]
  • “Quantifying Life” by Dmitry Kondrashov [link]
  • Rachel Fewster’s Stochastic Process courese notes [link]
  • Intro to Stochastic Processes course notes by Gordan Zitkovic [link]
  • “Statistical Thinking from Scratch: A Primer for Scientists” by Doc Edge [link]
  • “Pattern Recognition and Machine Learning” by Christopher Bishop [link]
  • “Probabilistic Graphical Models” by Daphne Koller [link]

Genetic Information Non-Discrimination and Privacy Protections

Here is a set of links for gaining more background on the topic of genetic non-discrimination and privacy collected by John in the period of 2018-2019. This list is focused on the recent history in the United States, and in particular focuses on understanding the 2008 Genetic Information Non-Discrimination Act and state-level laws that have been proposed or passed since GINA. Recommended updates are very welcome, and please email John (jnovembre at uchicago dot edu) with your suggestions.

  • General reference:
    • Council for Responsible Genetics’s Project page for Genetic Testing, Privacy, and Non-discrimination [link]
    • National Institutes of Health: “Genetic Discrimination and Other Laws” (2017) [link]
  • History and Descriptions of GINA: - The GINA bill text [link]
    • Selected press coverage and online materials:
      • “The new Genetic Information Genetic Nondiscrimination Act” by Jeremy Gruber (2009) [link]
      • “Politics and Perseverance: An interview with U.S. Rep. Louise Slaughter, D-N.Y.” (2009) [link]
      • Summary of the legislative history on revovly.com [link]
      • “Protecting Patients from Genetic Discrimination” by Joshua Kirsch (2017) in the Scientist [link]
      • “The Loopholes in the Law Prohibiting Genetic Discrimination” by Sarah Zhang (2017) in the Atlantic [link]
    • Organizational summaries of GINA:
      • American Society of Human Genetics: “GINA Turns 10” [link]
      • 23andme: “What Is GINA And Could My Genetic Data Make It Hard For Me To Get Insurance Coverage?” [link]
      • Coalition for Genetic Fairness: The coalition that pushed for GINA on a federal level [link]
  • Beyond GINA - Proposed or Passed state laws that cover more than GINA:
    • California’s “CalGINA”:
      • The CalGINA bill text [link]
      • History of CalGINA:
        • Overview of history on CalGINA by Jeremy Gruber [link]
        • “Considering the Impact of Yet Another Proposal for Genetic Legislation” by Dan Vorhaus (2011) The Privacy Report [link]
        • “A New Law to Raise GINA’s Floor in California” by Jennifer Wagner (2011) The Privacy Report [link]
        • Genetic Privacy Network project homepage: This page has an overview of concern, coverage, and laws related to genetic information non-discrimination and privacy. [link]
    • Massachusetts Genetic Bill of Rights (S. 1080):
      • The bill and status (stalled in 2011-2012 and not re-introduced) [link]
      • Summary via the Privacy Report from 2011: [link]
    • New York’s Assembly Bill A10229:
      • Prohibits insurance companies from discriminating based on genetic testing. Current status: in committee. [link]
    • The Canadian way forward, GNA 2017:
      • Overview from the Canadian Civil Liberties Association [link]
      • “Why insurers are wrong about Canada’s genetic non-discrimination law” Op-Ed by Mike Hoy, Economics, Guelph [link]
        • Supporting paper economic analysis by Mike Hoy: “The Potential Economic Impact of a Ban on the Use of Genetic Information for Life and Health Insurance” [link]
  • A new outcome from genetic information: Polygenic scores
    • “The personal and clinical utility of polygenic risk scores” by Torkomani, Wineinger and Topol (2018) Nature Reviews Genetics review article [link]
    • “Polygenic scores and tea drinking” by Graham Coop (2018) [link]
    • FAQs about “Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment”, Social Science Genetic Consortium (2018) [link]
    • “Tread Lightly Interpreting Polygenic Tests of Selection” by Novembre and Barton (2018) in Genetics [link]
  • Relevant academic articles:
    • Ethics
      • “Genetic Equity” by Harris & Sulston (2004) in Nature Reviews Genetics [link]
      • Genetics and Human Agency Project led by Eric Turkheimer (has numerous relevant posts on their blog) [link]
    • Law
      • “Genetic Information Nondiscrimination Act of 2008: It’s in Title VII’s Genes” by Vacchio and Wolinsky (2011) in Hofstra Labor & Employment Law Journal [link]
      • “The Genetic Information Nondiscrimination Act as an Antidiscrimination Law” by Jessica Roberts (2011) in Notre Dame Law Review [link]
      • “Genetic Data and Civil Rights” by Ifeoma Ajunwa (2016) in Harvard Civl Rights - Civil Liberties Law Review (CR-CL), Vol 51. [link]
      • University of Iowa project on Insurance Law & Genetics Research [link]
    • Medicine
      • “GINA, Genetic Discrimination, and Genomic Medicine” by Green, Lautenbach, McGuire (2015) in New England Journal of Medicine [link]
    • Social sciences
      • “The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, Our History, and the Future” by Conley and Fletcher (2017) [link]
  • Relevant recent coverage in the news:
    • “Genetic Discrimination Case Against School District is Appealed to Ninth Circuit” by Jennifer Wagner (2016) in the Privacy Report [link]
    • “Sociogenomics is opening a new door to eugenics” by Nathanial Comfort (2018) in Technology Review [link]
    • “The ‘geno-economists’ say DNA can predict our chances of success. Critics counter their methods are naive, offensive or both, but all agree: either way, multigene testing will lead to a social upheaval.” by Jacob Ward (2018) [link]