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PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD

Edward Gertz, Tero Hiekkalinna, Sébastien Le Digabel, Charles Audet, Joseph D Terwilliger, Alejandro A Schäffer

Article (2014)

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Background: PSEUDOMARKER is a software package that performs joint linkage and linkage disequilibrium analysis between a marker and a putative disease locus. A key feature of PSEUDOMARKER is that it can combine case- controls and pedigrees of varying structure into a single unified analysis. Thus it maximizes the full likelihood of the data over marker allele frequencies or conditional allele frequencies on disease and recombination fraction. Results: The new version 2.0 uses the software package NOMAD to maximize likelihoods, resulting in generally comparable or better optima with many fewer evaluations of the likelihood functions. Conclusions: After being modified substantially to use modern optimization methods, PSEUDOMARKER version 2.0 is more robust and substantially faster than version 1.0. NOMAD may be useful in other bioinformatics problems where complex likelihood functions are optimized.

Uncontrolled Keywords

Computational Biology; Disease; Gene Frequency; Genetic Linkage; Humans; Likelihood Functions; Linkage Disequilibrium; Pedigree; Sequence Analysis, DNA; Software

Department: Department of Mathematics and Industrial Engineering
Research Center: GERAD - Research Group in Decision Analysis
Funders: NIH- Intermural Research Program, NLM - Intermural Research Program, Air Force Office of Scientific Research, MimoMICS, Academy of Finland - DiDiPro Grant, BioSHaRE-EU, Paulo Foundation
Grant number: FA9550-12-0198, FP7-HEALTH-2012, NIH grants MH084995, NIH grants AG036469
PolyPublie URL: https://publications.polymtl.ca/3450/
Journal Title: BMC Bioinformatics (vol. 15)
Publisher: BioMed Central
DOI: 10.1186/1471-2105-15-47
Official URL: https://doi.org/10.1186/1471-2105-15-47
Date Deposited: 21 Jan 2019 16:00
Last Modified: 19 May 2023 20:23
Cite in APA 7: Gertz, E., Hiekkalinna, T., Le Digabel, S., Audet, C., Terwilliger, J. D., & Schäffer, A. A. (2014). PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD. BMC Bioinformatics, 15. https://doi.org/10.1186/1471-2105-15-47


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