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ProbABEL package for genome-wide association analysis of imputed data
Yurii S Aulchenko1, Maksim V Struchalin, Cornelia M van Duijn
1Department of Epidemiology, Erasmus MC, Postbus 2040, 3000 CA Rotterdam, The Netherlands. i.aoultchenko@erasmusmc.nl
BMC Bioinformatics
|March 18, 2010
Summary
The ProbABEL software package analyzes genome-wide imputed SNP data for complex traits. This tool efficiently handles imputation uncertainty, aiding in the identification of genetic loci.
Area of Science:
- Genetics
- Bioinformatics
Background:
- Genome-wide association (GWA) studies are crucial for identifying loci linked to complex traits.
- Imputed single nucleotide polymorphism (SNP) data are increasingly utilized in GWA analyses.
- Accurate analysis of imputed data requires methods that account for genotype imputation uncertainty.
Purpose of the Study:
- To develop the ProbABEL software package for analyzing genome-wide imputed SNP data.
- To provide a tool that addresses genotype imputation uncertainty in GWA studies.
Main Methods:
- The ProbABEL package supports quantitative, binary, and time-till-event outcomes using linear, logistic, and Cox proportional hazards models.
- It includes a fast two-step mixed model-based score test for association with quantitative traits in diverse sample types.
- Facilitates analysis in family-based studies, genetically isolated human populations, and outbred animal populations.
Main Results:
- ProbABEL offers a robust method for analyzing imputed SNP data in a genome-wide context.
- The software package is designed for speed and efficiency in handling large datasets.
- It supports various statistical models and population structures.
Conclusions:
- The ProbABEL package provides a fast and efficient method for analyzing imputed genome-wide data.
- This tool will accelerate the identification of genetic loci associated with complex traits.
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