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

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.

Documentation

Links