The Interdisciplinary Training Program in Statistical Genetics/Genomics and Computational Biology aims to train the next generation of quantitative genomic scientists to have a strong understanding of, and commitment to, cutting-edge methodological and collaborative research in statistical genetics/genomics and bioinformatics/computational biology with applications in genetic epidemiology, molecular biology and genomic medicine. We are committed to train trainees to become future quantitative leaders to develop and apply advanced, scalable statistical and computational methods to manage, analyze, integrate, and interpret massive integrated genetic and genomic, epidemiological and clinical data, to promote interdisciplinary research, and to effectively communicate and collaborate with subject-matter genomic researchers. In this renewal, we expand the scope of the program to enhance quantitative training in big ‘omics data science and reproducible research. The proposed training program has the following interrelated primary goals:

    • To provide high quality training in statistical theory and scalable computational methods that are needed to manipulate and analyze massive genetic and genomic data, and epidemiological and clinical data, to advance health science research and reproducible research;
    • To provide trainees with sufficient depth of knowledge and practical experience in molecular biology, genetic epidemiology, environmental genomics, and clinical genomics through coursework, lab rotations and research projects, so they can communicate and work effectively with subject-matter scientists.
    • To help trainees develop strong methodological and collaborative research skills needed to conduct successful interdisciplinary research by effectively collaborating with biologists, clinicians, and public health researchers, identifying important quantitative issues from real world ‘omics problems, quantitatively formulating problems, developing analytic methods and interpreting results;
    • To help trainees develop strong leadership and communication skills, engage them in a stimulating, nurturing and interactive environment, and provide them a range of rich career development opportunities, such as seminars, trainee-run retreats, professional conferences, and grant-writing.

The training grant directors are Xihong Lin (leading the statistical genetics and genomics element) and Curtis Huttenhower (leading the bioinformatics and computational biology element). Peter Kraft and John Quackenbush are associate directors.

Stipend and tuition support for this training program is funded through a National Institutes of Health grant (T32 GM74897).