Biography:Jeffrey T. Leek

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Short description: American biostatistician
Jeffrey T. Leek
Jeffrey Leek in 2017 (cropped).jpg
Jeffrey Leek in 2017
EducationUtah State University (B.S.)
University of Washington (Ph.D., M.S.)
Known forBiostatistics and Data Science
AwardsCOPSS Presidents' Award
Scientific career
FieldsBiostatistics
InstitutionsFred Hutchinson Cancer Research Center
Doctoral advisorJohn D. Storey
Doctoral studentsHilary S. Parker

Jeffrey Tullis Leek is an American biostatistician and data scientist working as a Vice President, Chief Data Officer, and Professor at Fred Hutchinson Cancer Research Center.[1][2] He is an author of the Simply Statistics blog, and runs several online courses through Coursera, as part of their Data Science Specialization.[3][4][5] His most popular course is The Data Scientist's Toolbox,[6] which he instructed along with Roger Peng and Brian Caffo. Leek is best known for his contributions to genomic data analysis and critical view of research and the accuracy of popular statistical methods.

Education

Leek graduated from Utah State University in 2003 with his Bachelors of Science. Then went on to study at the University of Washington achieving a Master's degree in 2005 and completed a PhD in Biostatistics in 2007 with John Storey as his doctoral advisor.[2][7]

Research and career

Leek joined Johns Hopkins University as an assistant professor in Biostatistics in 2009, working at the Bloomberg School of Public Health. In 2014 he became an associate professor in Biostatistics and Oncology.[8]

Leek works in The Center for Computational Biology[9] at Johns Hopkins University creating statistical packages[10][11] for analysis of genomes.

He also co-edits a blog, Simply Statistics[12] with Roger Peng and Rafa Irizarry, which contains a mix of articles on statistics and meta-research.

Leek has conducted several talks at prestigious universities and locations such as a colloquium series at Harvard[13] and a lecture at the New York Genome Center titled “Building a Comprehensive Resource for the Study of Human Gene Expression with Machine Learning and Data Science”[14] as a part of their lecture series.

He is an expert in reproducibility, and his work and opinions have been published in notable scientific and medical journals such as Nature[15][16] and the Proceedings of the National Academy of Sciences. Leek wrote a self-published book, The Elements of Data Analytic Style and is considered an expert on replication.[17][18]

He is currently Vice President and Chief Data Officer at Fred Hutchinson Cancer Center in Seattle, WA.[2]

Recognition

Leek was elected as a Fellow of the American Statistical Association in 2020.[19] In 2021, Leek won the COPSS Presidents' Award.[20]

Selected publications

Leek's highly cited works include

  • "Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis"[21]
  • "Tackling the Widespread and Critical Impact of Batch Effects in High-Throughput Data"[22]

References

  1. ↑ "Dr. Jeffrey Leek named VP and Chief Data Officer". 11 January 2022. https://www.fredhutch.org/en/news/center-news/2022/01/jeffrey-leek-vp-cdo.html. 
  2. ↑ 2.0 2.1 2.2 "Jeff Leek, Ph.D." (in en). https://www.fredhutch.org/en/faculty-lab-directory/leek-jeff.html. 
  3. ↑ "About". Simply Statistics. https://simplystatistics.org/about/. 
  4. ↑ Diane Peters (2018-02-22). "MOOCs are not dead, but evolving". University Affairs. https://www.universityaffairs.ca/news/news-article/moocs-not-dead-evolving/. 
  5. ↑ Steven Salzberg (2015-04-13). "How Disruptive Are MOOCs? Hopkins Genomics MOOC Launches In June". Forbes. https://www.forbes.com/sites/stevensalzberg/2015/04/13/how-disruptive-are-moocs-hopkins-genomics-mooc-launches-in-june/. 
  6. ↑ "Coursera - Data Scientists Toolbox". https://www.coursera.org/learn/data-scientists-tools. 
  7. ↑ "Simply Statistics: Interview with COPSS award Winner John Storey". https://simplystatistics.org/posts/2015-08-25-interview-with-copss-award-winner-john-storey/. 
  8. ↑ "Jeff Leek". LinkedIn. https://www.linkedin.com/in/jtleek/. 
  9. ↑ "Center for Computational Biology". Johns Hopkins University. http://ccb.jhu.edu/about.shtml. 
  10. ↑ "Software developed by Jeffrey Leek". http://www.biostat.jhsph.edu/~jleek/software.html. 
  11. ↑ "Software developed by The Center for Computation Biology". http://ccb.jhu.edu/software.shtml. 
  12. ↑ "Simply Statistics". https://simplystatistics.org/. 
  13. ↑ "What Can 20,000+ RNA-seq Samples Tell Us About How Much Of The Genome Is Transcribed?". Harvard Colloquium Seminar. 16 February 2016. https://www.hsph.harvard.edu/biostatistics/2016/02/colloquium-seminar-jeff-leek/. 
  14. ↑ Jeff Leek. "Building a Comprehensive Resource for the Study of Human Gene Expression with Machine Learning and Data Science.". New York Genome Center Lecture. http://www.nygenome.org/event-calendar/five-points-lecture-jeff-leek-phd/. 
  15. ↑ Leek, Jeff; Peng, Roger (2015-04-28). "Statistics: P values are just the tip of the iceberg". Nature 520 (7549): 612. doi:10.1038/520612a. PMID 25925460. Bibcode: 2015Natur.520..612L. 
  16. ↑ Leek, Jeff; McShane, Blakeley; Gelman, Andrew; Colquhoun, David; Nuijten, Michele; Goodman, Steven (2017-11-28). "Five Ways to Fix Statistics". Nature 551 (7682): 557–559. doi:10.1038/d41586-017-07522-z. 
  17. ↑ The Elements of Data Analytic Style. Leanpub. 20 February 2014. https://leanpub.com/datastyle. 
  18. ↑ Karen Nitkin (2017-11-07). "Could you repeat that? Fixing the 'replication crisis' in biomedical research has become top priority". Hub. https://hub.jhu.edu/2017/11/07/fixing-replication-crisis-in-science/. 
  19. ↑ "ASA Fellows list". American Statistical Association. https://www.amstat.org/ASA/Your-Career/Awards/ASA-Fellows-list.aspx. Retrieved 2020-06-01. 
  20. ↑ "Jeffrey T. Leek Wins COPSS Presidents’ Award | Amstat News" (in en-US). 2021-11-01. https://magazine.amstat.org/blog/2021/11/01/jeffrey-t-leek-wins-copss-presidents-award/. 
  21. ↑ Leek, Jeff; Storey, John (2007-09-28). "Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis". PLOS Genetics 3 (9): 1724–35. doi:10.1371/journal.pgen.0030161. PMID 17907809. 
  22. ↑ Leek, Jeff; Scharpf, Robert; Corrado Bravo, Hector; Simcha, David; Langmead, Benjamin; Johnson, Evan; Geman, Donald; Baggerly, Keith et al. (2010-10-01). "Tackling the Widespread and Critical Impact of Batch Effects in High-Throughput Data". Nature Reviews Genetics 11 (10): 733–9. doi:10.1038/nrg2825. PMID 20838408. 



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