Welcome to my website! I am a biostatistician at the University of Massachusetts Medical School. My research is in statistical methods for systems genetics. My colleagues and I use mice to study biology of complex traits, like body weight, that are affected by many genes and other factors. We design and perform experiments to map quantitative trait loci (QTL) with the goal of identifying gene regions that affect complex traits. I also maintain R packages that enable multivariate analysis in systems genetics studies.


Tomorrow my lab will participate in #ShutDownAcademia #ShutDownSTEM. I’ll stay at home instead of traveling to my office. And instead of doing my usual research, I’ll read, watch, and listen to pieces listed on the organizers’ website: https://www.shutdownstem.com/.

I hope that you’ll join me in participating.

Mathematician John Urschel recommended this article from the American Mathematical Society: https://www.ams.org/journals/notices/201802/rnoti-p149.pdf

I have the opportunity to present a poster at The Allied Genetics Conference (TAGC) 2020. I’ve posted both a pdf of the poster and a mp4 narrated video tour of the poster here.

I’d love to address your questions and hear your suggestions in the Q & A session on Thursday, April 30, at 1:30pm Eastern Time. My poster number is 1333A.

(Last modified: 2020-04-27 15:49:12)

qtl2pleio on CRAN

10 January 2020

CRAN now hosts the packages qtl2pleio and gemma2. qtl2pleio performs a d-variate, d-QTL scan over a select genomic region. gemma2 is used by qtl2pleio for the inference of multivariate variance components. They can be installed with: install.packages("qtl2pleio") The statistical model that qtl2pleio fits for each d-tuple of markers (or pseudomarkers) is \[ vec(Y) = Xvec(B) + vec(G) + vec(E) \] where \(Y\) is a n by d matrix of d traits (for each of n subjects), X is a dn by df block-diagonal matrix of founder allele probabilities, B is a f by d matrix of allele effects for each of d traits, G is a n by d matrix of polygenic random effects, and E is a n by d matrix of random errors.

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I have now completed ImprovBoston’s Improv Comedy 101 class. I’m happy to share the video of my class’s show from December 2019. You can view it here.

(Last modified: 2020-02-08 12:40:41)

I’ve followed a series of blog posts from Cal Newport at http://calnewport.com/blog/ (with posts like this) in which Newport criticizes social media platforms for, among other things, limiting the scope of internet browsing. Newport, a computer science professor and writer, proudly has never had a social media account. Until March 2018, I regularly consumed information from Facebook, Twitter, and even Instagram and Linkedin. Termination of these accounts aligned with my larger professional and scholarly goals of wanting to focus more on my studies and other, engaging, activities.

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Recent Works

  • Genetic Background Modifies Phenotypic Severity and Longevity in a Mouse Model of Niemann-Pick Disease Type C1. Jorge L. Rodriguez-Gil, Dawn E. Watkins-Chow, Laura L. Baxter, Gene Elliot, Ursula L. Harper, Stephen M. Wincovitch, Julia C. Wedel, Arturo A. Incao, Mylene Huebecker, Frederick J. Boehm, William S. Garver, Forbes D. Porter, Karl W. Broman, Frances M. Platt and William J. Pavan (2020) doi:10.1242/dmm.042614
  • qtl2pleio: Testing pleiotropy vs. separate QTL after Jiang & Zeng (1995). (2019)      
  • Testing pleiotropy in multiparental populations, Early career scientist seminar, Genetics Society of America, online, Oct 17, 2019  
  • gemma2: Multivariate random effects for systems genetics studies. (2019)      
  • Genetic determinants of gut microbiota composition and bile acid profiles in mice. Julia H. Kemis, Vanessa Linke, Kelsey L. Barrett, Frederick J. Boehm, Lindsay L. Traeger, Mark P. Keller, Mary E. Rabaglia, Kathryn L. Schueler, Donald S. Stapleton, Daniel M. Gatti, Gary A. Churchill, Daniel Amador-Noguez, Jason D. Russell, Brian S. Yandell, Karl W. Broman, Joshua J. Coon, Alan D. Attie and Federico E. Rey (2019) doi:10.1371/journal.pgen.1008073
  • qtl2pleio: Testing pleiotropy vs. separate QTL in multiparental populations. Frederick Boehm, Brian Yandell and Karl W. Broman (2019) doi:10.21105/joss.01435
  • Testing Pleiotropy vs. Separate QTL in Multiparental Populations. Frederick J. Boehm, Elissa J. Chesler, Brian S. Yandell and Karl W. Broman (2019) doi:10.1534/g3.119.400098
  • Testing pleiotropy in multiparental populations, Thesis defense, University of Wisconsin-Madison, Madison, Wisconsin, USA, Apr 21, 2019    
  • Testing pleiotropy in multiparental populations, International Mammalian Genomics Conference, Rio Mar, Puerto Rico, USA, Nov 6, 2018  
  • Testing pleiotropy in multiparental populations, Joint Statistical Meetings, Vancouver, British Columbia, Canada, Aug 1, 2018