Major efforts are under way to uncover the specific genetic components of many complex human disorders and quantitative traits. These efforts are generating an unprecedented wealth of data that requires sophisticated statistical analysis in order to maximize the information gleaned from each study. Likewise, many advances have been made in statistical methods for the study of complex genetic traits, and new statistical methods continue to be promulgated. To expedite and significantly advance the search for specific genes that predispose to these complex traits, we propose a series of annual hands-on short courses on statistical genetics and statistical genomics which will enable a far greater number of researchers, including clinical researchers, to participate in, contribute to, and lead such research. These short courses will help equip students, post-doctoral fellows, junior investigators and senior investigators new to the field with the statistical genetic approaches necessary to expedite genomic discovery. The courses will be taught by leading experts in statistical genetics/genomics. Each 5-day course will provide substantial """"""""hands-on"""""""" computer training that will effectively increase the number and the expertise of investigators who are pursuing genetic and genomic research. We expect approximately 50 students to attend each course, allowing for intensive interaction between students and faculty. Lectures will be supplemented with extensive discussion sessions, handouts, presentation of worked examples, and interactive demonstrations of statistical genetic data analyses. Finally, we will also initiate a new bursary service, providing funding for 10 course participants to travel to visit a course faculty member of their choice to help initiate or finish a particular project. This will provide an unprecedented collaborative opportunity for course participants and faculty.

Public Health Relevance

We propose an annual short course each year for 5 years on statistical genetics for investigators studying complex traits. Taught by leading experts in statistical genetics and genomics, these courses will be aimed at statisticians or non-statistician investigators who wish to learn both the 'language'of statistical genetics/genomics and the specific software used to analyze genetic and genomic data. Attendees should be either pursuing or in the early stages of a career in genetic/genomic research.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Education Projects (R25)
Project #
5R25GM093044-04
Application #
8478137
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Krasnewich, Donna M
Project Start
2010-08-01
Project End
2015-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
4
Fiscal Year
2013
Total Cost
$208,440
Indirect Cost
$15,440
Name
University of Alabama Birmingham
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Malik, Manasi; Chiles 3rd, Joe; Xi, Hualin S et al. (2015) Genetics of CD33 in Alzheimer's disease and acute myeloid leukemia. Hum Mol Genet 24:3557-70
Geng, Xin; Sha, Jin; Liu, Shikai et al. (2015) A genome-wide association study in catfish reveals the presence of functional hubs of related genes within QTLs for columnaris disease resistance. BMC Genomics 16:196
Enquobahrie, Daniel A; Moore, Amy; Muhie, Seid et al. (2015) Early Pregnancy Maternal Blood DNA Methylation in Repeat Pregnancies and Change in Gestational Diabetes Mellitus Status—A Pilot Study. Reprod Sci 22:904-10
Parikh, Ishita; Medway, Christopher; Younkin, Steven et al. (2014) An intronic PICALM polymorphism, rs588076, is associated with allelic expression of a PICALM isoform. Mol Neurodegener 9:32
Alexander, Eileen S; Martin, Lisa J; Collins, Margaret H et al. (2014) Twin and family studies reveal strong environmental and weaker genetic cues explaining heritability of eosinophilic esophagitis. J Allergy Clin Immunol 134:1084-1092.e1