Position title: Professor
Biostatistics and Medical Informatics
Statistical genetics and genomics
- 2126 Genetics-Biotechnology
- Ph.D., University of California at Berkeley (1997), Postdoctoral Research: Marshfield Medical Research Foundation, Marshfield, Wisconsin
- Lab Website
- Biostatistics and Medical Informatics
- Research Interests
- I work on statistical problems in genetics, genomics, and molecular biology, focusing particularly on characterizing of meiotic recombination and developing improved methods for detecting and identifying genes contributing to variation in complex traits in experimental organisms.
- Research Fields
- Computational, Systems & Synthetic Biology, Evolutionary & Population Genetics, Genomics & Proteomics, Human, mouse & rat
My research is entirely computational, though it is driven by close collaborations with numerous laboratory scientists, at UW-Madison and elsewhere. My work has three parts: data analysis, methods development, and software development. Data analysis is my passion; I love nothing more than a new set of data, with new questions and new puzzles. Few real problems can be addressed cleanly with old methods, and so new methods must be developed. My efforts in methods development are almost entirely persuaded by the problems and data that I have at hand, and my focus is always on the problem and the data; I have retained little interest in methods for the sake of methods. Finally, I expend a great deal of effort on software development. I enjoy computer programming, but this is again something that I do not for its own sake, but in order to properly analyze data. New data lead to new methods, and new methods require new computer programs.
The primary focus of my research is on the genetic analysis of complex traits. While I have worked on problems in human linkage analysis, the bulk of my efforts concern quantitative trait locus (QTL) mapping in experimental crosses (that is, mapping the genetic loci contributing to variation in quantitative traits). I have been involved in a variety of applications, largely in the mouse but also in other organisms. My methodological work has focused on the development of methods to identify multiple, interacting QTL, to tease apart the system of interacting loci that underlie a complex trait.
My second major focus has been the analysis of recombination at meiosis. Without recombination, genetic mapping, whether by linkage or association, would not be possible, and so even if the analysis of recombination were not useful, the process would still deserve careful study. I have constructed genetic linkage maps in a variety of organisms, but my main interest is in characterizing crossover interference and individual and sex-specific variation in recombination.
Search PubMed for more publications by Karl Broman
Broman KW (2015) R/qtlcharts: interactive graphics for quantitative trait locus mapping. Genetics 199:359-361
Kwak I-Y, Moore CR, Spalding EP, Broman KW (2014) A simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. Genetics 197: 1409-1416
Broman KW, Kim S, Sen Ś, Ané C, Payseur BA (2012) Mapping quantitative trait loci onto a phylogenetic tree</a>. Genetics 192:267-279
Broman KW (2012) Genotype probabilities at intermediate generations in the construction of recombinant inbred lines. Genetics 190:403-412
Broman KW (2012) Haplotype probabilities in advanced intercross populations. G3 2:199-202