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GADS software for parametric linkage analysis of quantitative traits distributed as a point-mass mixture
Tatiana I Axenovich1, Irina V Zorkoltseva
1Institute of Cytology & Genetics, Siberian Division, Russian Academy of Sciences, Novosibirsk 630090, Russia. aks@bionet.nsc.ru
Computational Biology and Chemistry
|February 21, 2012
Summary
This study introduces GADS, a new software for quantitative trait linkage analysis in proteomics and metabolomics data with distribution spikes. It successfully identified a significant linkage signal for vertical cup-to-disc ratio on chromosome 6.
Area of Science:
- Genetics
- Bioinformatics
- Ophthalmology
Background:
- Quantitative trait mapping often faces challenges with data exhibiting irregular distributions, particularly a spike.
- Existing human quantitative trait loci (QTL) mapping methods are not suitable for such data, necessitating sample reduction and analysis of only continuous measurements.
Purpose of the Study:
- To propose a novel method for parametric linkage analysis of traits with a spike in their distribution.
- To introduce GADS, a software package implementing this method and including complex segregation analysis for parameter estimation.
Main Methods:
- Development of a parametric linkage analysis method for trait distributions with a spike.
- Implementation of the method in the GADS software, incorporating complex segregation analysis.
- Application of the method to real-world data on vertical cup-to-disc ratio in a Dutch pedigree.
Main Results:
- GADS identified a significant linkage signal on chromosome 6 for vertical cup-to-disc ratio.
- Analysis of only the normally distributed portion of the data yielded only a suggestive linkage peak, highlighting the advantage of the new method.
- The proposed method effectively handles traits with spiked distributions.
Conclusions:
- The GADS software and its underlying method provide a powerful tool for linkage analysis of complex traits with spiked distributions.
- This approach enhances the ability to detect genetic associations in omics studies where data irregularities are common.
- The findings have implications for understanding genetic factors in conditions like glaucoma, using traits such as the vertical cup-to-disc ratio.
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