PedPeel
PedPeel computes optimal peeling orders for zero-loop pedigrees with incomplete genotypic information to minimize computational complexity during likelihood calculations for linkage analysis and genetic parameter estimation.
Key Features:
- Optimal Peeling Order: Uses a graph-theoretic algorithm to determine an optimal peeling order for zero-loop pedigrees with incomplete genotypes, minimizing the number of likelihood calculations required.
- Handling Complex Pedigrees: Specifically tailored to zero-loop pedigrees where traditional approaches may struggle to find efficient peeling orders, thereby reducing computational burden in linkage analysis.
- Integration with Existing Software: Compatible with software that uses the Elston–Stewart algorithm for likelihood calculations, enabling use of optimized peeling orders within Elston–Stewart evaluations.
Scientific Applications:
- Linkage Analysis: Facilitates testing for linkage across multiple marker loci by reducing computational demands for likelihood-based analyses.
- Genetic Parameter Estimation: Improves computational feasibility of precise estimation of genetic parameters in family-based studies with incomplete genotypes.
- Large Family Pedigree Analysis: Supports analysis of large family datasets with complex zero-loop pedigrees by reducing computational inefficiencies.
Methodology:
A graph-theoretic algorithm systematically selects the most efficient peeling order for zero-loop pedigrees with incomplete genotypic data to minimize the number of likelihood calculations.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Perl
- Added:
- 8/3/2017
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Statistical calculation
Outputs
Other operations do not define inputs or outputs.
Publications
Belonogova NM, Axenovich TI. Optimal peeling order for pedigrees with incomplete genotypic information. Computational Biology and Chemistry. 2007;31(3):173-177. doi:10.1016/j.compbiolchem.2007.03.004. PMID:17500037.
PMID: 17500037