| EPSRC Reference: |
GR/S18786/01 |
| Title: |
Variational-based methods for inference in population genetics |
| Principal Investigator: |
Fearnhead, Professor P |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Mathematics and Statistics |
| Organisation: |
Lancaster University |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 January 2004 |
Ends: |
31 December 2006 |
Value (£): |
147,620
|
| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
|
|
| EPSRC Industrial Sector Classifications: |
| Environment |
Healthcare |
| Pharmaceuticals and Biotechnology |
No relevance to Underpinning Sectors |
|
| Related Grants: |
|
| Panel History: |
| Panel Date | Panel Name | Outcome |
|
29 Nov 2002
|
Mathematics Prioritisation Panel (Science)
|
Deferred
|
|
|
Summary on Grant Application Form |
|
Recent advances in molecular biology have led to an explosion in the amount of DNA sequence and SNP data documenting genetic variability within and between populations. There is a need for efficient statistical tools for analyzing this data. Existing approaches either use computational techniques to approximate the true likelihood surface, or make (oftern large-scale) approximations to the likelihood surface, with a view to making the resulting pseudo-likelihood curve easier to calculate. The former methods, while optimal, appear impracticable for the large data sets that are being, and will be, generated. The latter methods are inefficient as they involve throwing away some of the information in the data. This project focusses on developing novel and innovative ways for approximating the true likelihood, based on variational methods. An initial study suggests such approaches have great promise: accurate estimates of recombination rates have been obtained from large data sets, at small computational cost. Variational methods will be developed for analysing realistic large data sets, for example SNP data with only genotypic information, with particular emphasis on detecting local recombination-hotspots. The performance of such methods will be evaluated both via detailed simulation studies, and through a theoretical study of the accuracy of variational methods.
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.lancs.ac.uk |