NIGMS T32 Interdisciplinary Biostatistics Training in Genetics and Genomics

NIGMS T32 Interdisciplinary Biostatistics Training in Genetics and Genomics (T32 GM132063, 2020--2025)

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Directors/PIs: Saonli Basu and Wei Pan
Summary: This is an updated version of our previous T32 program. The primary mission of this training grant is to prepare Biostatistics predoctoral trainees for leadership roles in biomedical and public health research through excellent training and mentorship in genetics and genomics. Our specific objectives include completion by each trainee of required and elective coursework in our PhD program and in other departments, mentored learning through interdisciplinary research projects, development of communication and networking skills, attendance at and participation in journal clubs and seminars, and successful completion of a program of interdisciplinary research through their dissertation, all of which give our trainees broad training in a rapidly expanding field. The distinctive feature of the proposed training program is that each objective has both a biostatistical aspect and a biomedical aspect. A key is to ensure each trainee learns how to carry out a cohesive and interdisciplinary research program, including working with biomedical researchers, and writing, submitting, editing, and resubmitting scholarly papers. The program is designed to support students for up to two years at the early stages of their PhD studies, after which their support will switch to projects funded by the faculty mentors' research grants.
Program-specific training requirements:
- Registration in Journal Club in Statistical Genetics and Genomics for four semesters (to be set up as a 1 credit class per semester), and participation in all remaining semesters;
- If no previous biology background yet, strongly encouraged to take two TG-specific electives in computational or experimental biology (total 6 credits).
- Biostat/Stat students: an ethics course (e.g. Biomedical Ethics, BTHX 5325, 3 credits, recommended); two required courses in Statistical Genetics/Genomics or Machine Learning: PUBH 8445 Statistics for Human Genetics and Molecular Biology, 3 credits, past syllabus, and one of the following two, PUBH 8446 Advanced Statistical Genetics and Genomics, 3 credits, past syllabus, and PUBH 8475 Statistical Learning and Data Mining; both can be counted as Biostatsitics electives.
- Non-Biostat/Stat students: Each PhD program has its own required coursework. Each trainee from a non-biostatistics/statistics PhD program is required to take a minor in Biostatistics, in addition to the requirement from his/her home program. The requirements of the Biostatistics Minor program for a non-statistics PhD students are listed here . In summary, the T32-specific requirements are the following:
  1. As a part of the Biostatistics Minor program, one is required to have a Biostatistics faculty member as his/her dissertation committee; for a T32 trainee from a non-biostatistics PhD program, this Biostatistics faculty member is expected to be a T32 trainer;
  2. As a part of the Biostatistics Minor program, one is required to take two required and two elective Biostatistics classes; the following two elective courses are required for T32 trainees from a non-biostatistics PhD program (and are counted as two of their four courses required for the Biostatistics Minor program): PUBH 7445, Statistics in Genetics and Molecular Biology, 3cr, and PUBH 7475, Statistical Learning and Data Mining, 3 cr;
  3. Participation in Journal Club in Statistical Genetics and Genomics and other T32 activities every semester.
Faculty trainers: (for any email address with a missing component after @, please add umn.edu after @)
Methods Mentors:
- Wei Pan, PhD, Biostatistics; Email: panxx014@
- Saonli Basu, PhD, Biostatistics; saonli@
- Mark Fiecas, PhD, Biostatistics; mfiecas@
- Weihua Guan, PhD, Biostatistics; wguan@
- Rui Kuang, PhD, Computer Sci&Eng; kuang@cs.umn.edu
- Eric Lock, PhD, Biostatistics; elock@
- Chad Myers, PhD, Computer Sci&Eng; cmyers@cs.umn.edu
- James Neaton, PhD, Biostatistics; jim@ccbr.umn.edu
- Cavan Reilly, PhD, Biostatistics; cavanr@biostat.umn.edu
- Xiaotong Shen, PhD, Statistics; xshen@
- Sandra Safo, PhD, Biostatistics, ssafo@
- Baolin Wu, PhD, Biostatistics; baolin@biostat.umn.edu
- Tianzhong Yang, PhD, Biostatistics; yang3704@
- Lin Zhang, PhD, Biostatistics; zhan4800@
Biomedical Co-Mentors:
- Frank Albert, PhD, Genetics, Cell Biology & Development; Email: falbert@
- Ran Blekhman, PhD, Genetics, Cell Biology & Development; Ecology, Evolution & Behavior; blekhman@
- Lin Yee Chen, MD, Medicine; chenx484@
- Pamala Jacobson, Pharm D, Pharmacy; jacob117@
- Ling Li, PhD, Pharmacy; lil@
- Matt McGue, PhD, Psychology; mcgue001@
- Jim Pankow, PhD, Epidemiology; panko001@
- Nathan Pankratz, PhD, Laboratory Medicine and Pathology; pankr018@
- Logan Spector, PhD, Pediatrics; spect012@
- Weihong Tang, PhD & MD, Epidemiology; tang0097@
- Christine Wendt, MD, Medicine; wendt005@
Student Outcome Data: TBA

Tranees: (usually junior) PhD students in Biostatistics or an affilated program at the University of Minnesota; US citizens or permanent residents; excellent academic records; strong interests in computation and analysis of genetic or genomic data.
Interested applicants, especially under-represented minority students and students with disabilities, are encouraged to contact the PI Dr Wei Pan via email: panxx014@

Journal Club: schedule.

More NIGMS T32 information. In partciluar, from "Answers to Institutional Predoctoral Training Grants (T32) Frequently Asked Questions":
Q. Does NIGMS provide travel funds for T32 predoctoral trainees?
A. Yes, NIGMS pays a flat rate of $300 per trainee per year for travel.
Q. Can we request costs for family health insurance for trainees?
A. Tuition, fees and health insurance (self-only or family) are allowable trainee costs only if such charges are applied consistently to all people in a similar training status at the organization, without regard to their source of support. Health insurance can include coverage for costs such as vision and/or dental care if consistent with organizational policy. Health insurance is awarded as part of the Training Related Expenses category.