Streamlining Big Genomic Data Analysis and Knowledge Extraction
Lead Research Organisation:
University of Edinburgh
Department Name: The Roslin Institute
Abstract
Background
Nucleic acid genotyping and sequencing technology has transformed livestock genetics and animal breeding, and offers exciting new opportunities to understand how traits of interest to animal production are controlled at the genomic level. Breeding organisations have embraced this new opportunity and have established genomic evaluation programs across different farm animal species, in which a huge volume of data is generated on a routine basis. As big genomic data rapidly accumulates, an inherent barrier to the effective uptake and use of the new technology emerges due to the complexities of managing such a large volume of information. On the same time, the unprecedented quantity and quality of these genomic repositories presents a unique opportunity to use them to unravel the complexities of the biological process that underlie the phenotypic expression of economically important traits.
Aims
The overarching aim of the project is to develop the strategies and a data-centric framework to optimise the analysis of big genomic repositories and extract novel biological knowledge.
The following aims will be addressed:
- Identify genomic variants and regions that explain genetic variation for a variety of traits and across different chicken lines.
- Create a curated database that collects and processes data from online repositories via the respective APIs and integrates them with in-house results.
- Streamline the process of combining results from meta-analysis and functional information to rank the results of statistical association with an ultimate objective to strengthen causal interference.
Nucleic acid genotyping and sequencing technology has transformed livestock genetics and animal breeding, and offers exciting new opportunities to understand how traits of interest to animal production are controlled at the genomic level. Breeding organisations have embraced this new opportunity and have established genomic evaluation programs across different farm animal species, in which a huge volume of data is generated on a routine basis. As big genomic data rapidly accumulates, an inherent barrier to the effective uptake and use of the new technology emerges due to the complexities of managing such a large volume of information. On the same time, the unprecedented quantity and quality of these genomic repositories presents a unique opportunity to use them to unravel the complexities of the biological process that underlie the phenotypic expression of economically important traits.
Aims
The overarching aim of the project is to develop the strategies and a data-centric framework to optimise the analysis of big genomic repositories and extract novel biological knowledge.
The following aims will be addressed:
- Identify genomic variants and regions that explain genetic variation for a variety of traits and across different chicken lines.
- Create a curated database that collects and processes data from online repositories via the respective APIs and integrates them with in-house results.
- Streamline the process of combining results from meta-analysis and functional information to rank the results of statistical association with an ultimate objective to strengthen causal interference.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/S508032/1 | 01/10/2018 | 31/08/2023 | |||
| 2105617 | Studentship | BB/S508032/1 | 01/09/2018 | 31/08/2022 |