Statistical Bioinformatician
Lead Research Organisation:
Roslin Institute
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
Working with colleagues in Numerical Genetics at Roslin Institute, the major objective of this project is to assist with use of bioinformatic tools and extraction and analysis of genomic data. The main areas of technical expertise required are in bioinformatics, genomic analysis and statistics. Tasks the postholder undertakes or oversees include: Extraction and interpretation of data from genomic (e.g. sequence, protein, EST, etc) databases. Sequence analysis. Combining information from several databases and other sources using self-written utilities. Analysis of high-throughput genomics data (e.g. SNPs, microarrays). Integration of genetic (e.g. linkage, association) results with bioinformatic resources. Learning and critically evaluating new software tools and packages. Liaison with other members of the project teams and contributing to overall project progress. Reporting of findings to project scientists, funders and other stakeholders Drafting scientific publications arising from this work. Documentation of results obtained and the process by which they were obtained. Contributing to supervision of PhD and other students and visitors. Contributing to training for staff, students and visitors. Additionally, the postholder contributes to the development of new research projects in this field including contributing to new grant applications, keep abreast of the relevant scientific literature and attend scientific seminars and meetings.
Planned Impact
unavailable
Organisations
People |
ORCID iD |
| Dirk De Koning (Principal Investigator) |
Publications
Crooks L
(2009)
Comparison of analyses of the QTLMAS XII common dataset. II: genome-wide association and fine mapping.
in BMC proceedings
De Koning DJ
(2007)
Genetical genomics: combining gene expression with marker genotypes in poultry.
in Poultry science
Ekine C
(2014)
Why Breeding Values Estimated Using Familial Data Should Not Be Used for Genome-Wide Association Studies
in G3 Genes|Genomes|Genetics
Hadjipavlou G
(2010)
Extensive QTL and association analyses of the QTLMAS2009 Data.
in BMC proceedings
Jaffrezic F
(2009)
The EADGENE and SABRE post-analyses workshop
in BMC Proceedings
Karacaƶren B
(2011)
Association analyses of the MAS-QTL data set using grammar, principal components and Bayesian network methodologies.
in BMC proceedings
Lam AC
(2009)
A combined strategy for quantitative trait loci detection by genome-wide association.
in BMC proceedings
Lund MS
(2009)
Comparison of analyses of the QTLMAS XII common dataset. I: Genomic selection.
in BMC proceedings
Rowe SJ
(2009)
Detecting parent of origin and dominant QTL in a two-generation commercial poultry pedigree using variance component methodology.
in Genetics, selection, evolution : GSE
Rowe SJ
(2008)
Detecting dominant QTL with variance component analysis in simulated pedigrees.
in Genetics research
| Description | This post has been highly valuable in supporting the PI in ongoing projects. The work has been linked to several other BBSRC funded projects as well as EC projects. |
| Exploitation Route | The results are followed up in each of the individual projects. The two researchers who held this post have both moved on to senior research positions in other Universities or Research Institutes. |
| Sectors | Agriculture Food and Drink |
| Description | Results from boar taint research are being used in practial pork breeding. |
| First Year Of Impact | 2012 |
| Sector | Agriculture, Food and Drink |
| Impact Types | Societal Economic |