Project description
Scalable genealogical and statistical methods for genomic analysis
Large health and genetics studies now contain genomic, health and environmental data from millions of individuals, creating major computational and statistical challenges. The ERC-funded ARGgen project will develop scalable methods to analyse these datasets more efficiently and accurately. It will reconstruct large-scale genealogical graphs to represent evolutionary relationships among modern and ancient genomes and use them to improve genomic analyses, model genetic ancestry and study human evolutionary history. The project will also develop machine-learning methods to extract information about biological function from genomic data, analyse multiple traits and ancestries, and support cross-biobank analyses. These methods will be released as high-quality open-source software, enabling researchers to analyse increasingly large and diverse genomic datasets.
Objective
Biobank datasets, containing genomic, environmental, and health data for millions of individuals, have provided insights into disease susceptibility, biological mechanisms, and human evolution, facilitating applications such as drug development and genetic risk prediction. However, these datasets present significant challenges: processing their large volumes is computationally very demanding, and modeling the heterogeneity they contain poses substantial statistical obstacles. These issues risk leaving genomic datasets underutilized or amplifying existing biases, such as those linked to genetic ancestry.
To address these challenges, this proposal will develop scalable statistical methods to reduce computational costs, improve the modeling of genetic ancestry, and increase accuracy and statistical power across several genomic analyses. We will focus on three specific aims. First, we will develop scalable methods to reconstruct large-scale genome-wide genealogical graphs, capturing evolutionary relation-ships and enabling applications such as simulation, phasing, imputation, and data sharing. Second, we will extend this framework to analyze both ancient and modern genomes, using genealogical graphs to define new ancestry descriptors and study human evolutionary history at fine resolution. Finally, we will create Bayesian machine learning approaches to improve the detection of trait- and disease-associated variants, model multiple traits and ancestries, learn biological function from raw genomic data, and enable distributed cross-biobank analyses. We will implement these models as high-quality, freely available open-source software.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- humanities history and archaeology history
- natural sciences biological sciences genetics genomes
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
OX1 2JD Oxford
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.