Core Resources : Genetic Epidemiology Core
Genetic Epidemiology Core
Contact: Susan Slifer
sslifer@med.miami.edu
The CGESG provides state-of-the-art analytic methodology to discover human disease genes. The Center includes faculty researchers with expertise in genetic epidemiology and statistical genetics as they relate to human disease.
Genetic Epidemiology Core
The Section of Genetic Epidemiology in the CGESG includes faculty involved in the research of human genetic disease with a focus on analytic approaches. The section houses the Genetic Epidemiology Core. Areas of interest include:
- Disease-gene mapping studies
- Environmental factors in genetic diseases
- Pharmacogenomics
- Cohort studies
- Family studies
- CNV analysis
- Sanger sequencing
- Next Generation sequencing
The Genetic Epidemiology Core provides all aspects of genetic analysis in human disease-gene mapping including preprocessing, statistical analysis and post-processing of genetic and related phenotypic data. Core Leader, Susan Slifer, who has over 15 years of experience in genetic analysis, coordinates core members and processes of the Core with guidance by the CGESG Faculty. Ms. Slifer works with the Statistical Programming Core and the HIHG Informatics Core to maintain data processing and statistical analysis software. The Core has available experienced analysis teams. Analysis teams are composed of statistical analysts who work closely with the project PI on study design, analysis conception, implementation and interpretation, and also assist in data management, analysis and reporting of results.
Software for data analysis and computer simulation is available on our Linux servers. Most common genetic analysis programs are available on these machines, as well as standard statistical software such as SAS, R, and SPSS. In addition, two Linux clusters with a total of more than 5000 processors are available and maintained by the Center for Computational Science at UM.
The GESG manages analysis of both family data and population-based case-control data, and is skilled at managing high-throughput genotype data in large data sets. Integration between different centers (the GESG Center, the Molecular Genetics Center, Clinical and Laboratory Informatics Center, and Bioinformatics) is another feature and provides a seamless flow of laboratory and clinical data through analysis.
The GESG Center performs the following essential functions for HIHG and their collaborators:
Study design
Assessment of project needs, clinical resources and statistical power analyses are used to develop study design.
Quality-control analysis
Quality-control programs developed in-house rigorously assess data entry and laboratory errors.
Linkage and association analysis
Genetic analysis for different types of family-based and case-control datasets is able to be conducted in HIHG using a multi-analytic strategy including:
- In-house developed software
- Publicly available programs
- Parametric and nonparametric linkage analysis
- Family-based association tests
- GWAS analysis programs
- Imputation
- General statistical software
Gene-gene and gene-environment analysis
We provide expertise in analysis of gene-gene and gene-environment interactions in case-control and family data.
Analysis of gene expression data
Statistical analysts in the CGESG have experience in analysis and interpretation of expression data from SAGE and microarrays.
CNV analysis
We provide Copy number (CNV) analysis of genome-wide data for both family-based and case-control studies.
Sequencing analysis
Analysis of Sanger and Next-Gen sequencing results is performed with coordination of the HIHG’s Bioinformatics group.
A multi-analytic strategy is applied in the Center to provide a deeper and better understanding of the data as well as greater confidence in study results. The Center has established an extensive suite of analysis programs developed by our faculty and other researchers. The faculty and staff of the CGESG continually endeavors to assess, develop and apply for new methods to solve the encountered problems from the ongoing studies to ensure that our analysis capabilities remain state of the art and make our software development standard and applicable around the world.