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Spencer Muse

Professor

SAS Hall 5276

Bio

Education

Ph.D Statistics and Genetics North Carolina State University 1993

Area(s) of Expertise

  • Bioinformatics
  • Statistical Genetics

Publications

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Grants

Date: 07/01/23 - 6/30/24
Amount: $191,391.00
Funding Agencies: National Institutes of Health (NIH)

The Environmental Health Bioinformatics (EHB) T32 training program leverages the unique confluence of strengths in Data Science and Environmental Health Science at NC State to train scientists fluent in this critical interdisciplinary space. The program includes several enhancements to further the environment for mentored research training and professional development. This data-intensive training program will produce scientists ready to meet the emerging challenges in environmental health research, including the ever-expanding exposome, understanding of variability between individuals, rational integration across massive data sets, and study designs that incorporate diverse community goals and needs.

Date: 07/01/00 - 6/30/22
Amount: $5,890,438.00
Funding Agencies: National Institutes of Health (NIH)

The graduate training program in Bioinformatics at North Carolina State University requests support for 10 pre-doctoral trainees and 2 post-doctoral trainees. These trainees work at the interface of genomic science, computer science and statistics.

Date: 09/10/15 - 8/31/20
Amount: $336,495.00
Funding Agencies: National Institutes of Health (NIH)

Funds from this project will support the continued development of the HyPhy software system for statistical analyses of genetic sequence data. This software originated in the Muse lab and has been under continuous development since 1996. The specific work for this project will include: • Development of new statistical methodology for statistical analyses of protein-coding DNA sequences, with emphasis on Bayesian model averaging approaches. • Guidance in the overall design and implementation of new HyPhy elements and features. • Maintenance and documentation of the HyPhy system, in collaboration with our UCSD collaborators.

Date: 07/01/12 - 6/30/20
Amount: $1,707,998.00
Funding Agencies: National Institutes of Health (NIH)

This project will support the training of six predoctoral students each year in the area of biostatistics, with an emphasis on applications to modern problems in genomic science. The training combines rigorous coursework in statistical methods and theory, additional courses in bioinformatics and genomic science, and an extensive laboratory training experience. For the latter, trainees will begin as supervised statistical consultants for a matched genomics lab, then over the course of a year progress into active collaborators in one or more lab projects. Most students will be supported for the first three years of their graduate programs. The scientific training will be supplemented with training in the responsible conduct of research developed specifically to meet the needs of researchers in this area. The training involves collaboration among biostatistics, genomics, and philosophy faculty members. An active recruiting plan is described for enhancing the diversity of our training and graduate programs, including a summer program bringing faculty and undergraduate students from minority serving institutions to NC State during the summer to initiate collaborative work with training faculty.

Date: 02/01/17 - 1/31/20
Amount: $286,235.00
Funding Agencies: RTI International (aka Research Triangle Institute)

This joint proposal from RTI and NCSU seeks to create a multi-faceted three-year Program in Genetic Discovery and Prediction (PGDP), initially organized around a demonstration and feasibility pilot for a highly ambitious effort the team calls the “1000 GWAS Project.” The Project will compile an unprecedented number of publicly available genome-wide association studies (GWAS, representing hundreds of thousands of patients). These studies have been used to identify genetic variants that predispose humans to disease and can be used to predict patient outcomes. The Project will re-analyze the combined data using the latest methods for genetic analysis and quality control, combined with new linkages to standard measures for phenotypes, as well as data on clinical covariates and exposures. In addition, the team will make progress on a GWAS Connector tool to support exploration and prioritization of dbGaP phenotypes for enriched secondary analysis. Finally, the Project will feed back into public repositories, providing an open-source analysis pipeline and community resource for ongoing research. The unprecedented data compilation and comprehensive analysis will reveal subtle and more complex interactions between genes, environmental exposures and resulting disease and treatment outcomes.

Date: 09/15/10 - 9/09/15
Amount: $1,111,400.00
Funding Agencies: National Institutes of Health (NIH)

HyPhy is a software system developed over the past decade by the PI, Spencer Muse, and his collaborators. HyPhy allows biological researchers to quickly develop and apply new statistical methods for analyzing DNA and other types of genetic data when it is collected from multiple species. Applications of HyPhy include biomedical research, where understanding the mode of viral evolution is useful in understanding how viruses escape the immune response and/or therapeutic treatments, as well as basic biological research, where HyPhy might be used to help a researcher decipher the evolutionary relationships of a group of species.The proposed work will provide support for enhancing the robustness and functionality of the software.

Date: 07/01/07 - 6/30/12
Amount: $744,577.00
Funding Agencies: National Institutes of Health (NIH)

The training plan in this proposal is designed to provide biostatisticians with the necessary skills to function quickly and effectively in today's multidisciplinary, team-oriented biomedical research environment, applicable to career paths in academia, government, and industry. The training plan takes advantage of existing strengths in interdisciplinary research and training at North Carolina State University (NCSU), and consists of the following major components: 1. A curriculum tailored to the demands of working at the interface of biostatistics and genomics. The coursework will provide rigorous training in statistical theory and practice, but will also include courses in basic genetics, genomic science, and bioinformatics, as well as elective courses tailored to each student?s interests. 2. A suite of activities designed to foster interdisciplinary training and collaboration: a. A group of biological labs will, on a rotating basis, host the trainees and training faculty in a scheduled lab meeting tailored to introduce the research in those labs. b. Trainees will have an extended laboratory "genomics immersion" during their second and third years. The lab meetings will facilitate finding good matches between labs and students. c. Required involvement in an interdisciplinary journal club series . d. Immediate assignment to new students of a mentorship team including both biological and statistical faculty. 3. Degree paths leading to the PhD in either Statistics or Bioinformatics, depending on the strengths and interests of the student. Students in both options will share a core set of courses designed to provide essential training in statistics, genomic science, and bioinformatics, and to enhance the sense of student community.

Date: 03/10/05 - 6/30/10
Amount: $270,000.00
Funding Agencies: University of North Carolina System Office (formerly UNC - General Administration)

We propose to develop a new PhD curriculum for training in Statistical Genetics. The program will take advantage of NC State's unique and historical strengths in the applications of rigorous statistical theory to solve problems arising from the influx of genetic data. The training program will include coursework in statistics and genetics, and it will include a new and novel laboratory component in which trainees spend time working side by side with molecular geneticists in the campus Genome Research Lab (GRL). In this laboratory setting students will become familiar with the technology and protocols for data generation, providing them with improved ability to develop new methods of statistical analysis. In addition, the students will act as consultants (under the supervision of statistical genetics faculty) for the empirical projects in the GRL. The training program, therefore, integrates theoretical study designed to allow students to address problems arising from empirical projects in which they are active collaborators. Such a program is unique in the history of NC State, and to our knowledge no such program exists at any other university. The continuing historical strengths of NC State in both Statistics and Genetics, and especially in their intersection, provides a unique opportunity for our faculty to provide gradaute training that will produce students highly qualified for industrial, government, and academic positions in an important emerging discipline.


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