GADS
GADS performs parametric linkage analysis integrated with complex segregation analysis to analyze quantitative traits with spiked or irregular distributions for genetic mapping in proteomics, metabolomics and human QTL studies.
Key Features:
- Parametric Linkage Analysis: Implements a parametric linkage analysis method tailored for traits with spiked distributions, allowing inclusion of spike-related data that conventional approaches often exclude.
- Complex Segregation Analysis: Performs complex segregation analysis to estimate genetic model parameters required for accurate linkage studies.
- Application to Large Pedigrees: Supports analysis of large pedigrees without loops for extensive family-based genetic investigations.
- Real-World Validation: Validated on vertical cup-to-disc ratio data, an optic disc characteristic linked to glaucoma, in a Dutch isolated population and demonstrated detection of linkage signals missed by methods restricted to normally distributed data.
Scientific Applications:
- Proteomics and Metabolomics: Supports genetic mapping of quantitative molecular traits measured in proteomics and metabolomics studies that exhibit spiked distributions.
- Human QTL Mapping: Applies to human Quantitative Trait Loci (QTL) mapping when traits violate normal distribution assumptions due to spikes.
- Ophthalmic Genetics: Enables linkage analysis of optic disc measures such as vertical cup-to-disc ratio relevant to glaucoma genetics.
Methodology:
GADS applies parametric linkage analysis integrated with complex segregation analysis to estimate genetic model parameters and include data points contributing to spiked trait distributions.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows
- Programming Languages:
- Perl, Fortran
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Axenovich TI, Zorkoltseva IV. GADS software for parametric linkage analysis of quantitative traits distributed as a point-mass mixture. Computational Biology and Chemistry. 2012;36:13-14. doi:10.1016/j.compbiolchem.2011.11.004. PMID:22340440.
PMID: 22340440