FRANz

Reconstruction of wild multi-generation pedigrees

Markus Riester, Peter F. Stadler, Konstantin Klemm

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

Summary: We present a software package for pedigree reconstruction in natural populations using co-dominant genomic markers such as microsatellites and single nucleotide polymorphisms (SNPs). If available, the algorithm makes use of prior information such as known relationships (sub-pedigrees) or the age and sex of individuals. Statistical confidence is estimated by Markov Chain Monte Carlo (MCMC) sampling. The accuracy of the algorithm is demonstrated for simulated data as well as an empirical dataset with known pedigree. The parentage inference is robust even in the presence of genotyping errors.

Original languageEnglish
Pages (from-to)2134-2139
Number of pages6
JournalBioinformatics
Volume25
Issue number16
DOIs
Publication statusPublished - Aug 2009
Externally publishedYes

Fingerprint

Pedigree
Nucleotides
Polymorphism
Software packages
Microsatellite Repeats
Markov processes
Microsatellites
Markov Chains
Monte Carlo Sampling
Single nucleotide Polymorphism
Prior Information
Sampling
Markov Chain Monte Carlo
Software Package
Single Nucleotide Polymorphism
Confidence
Genomics
Software
Population

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability

Cite this

FRANz : Reconstruction of wild multi-generation pedigrees. / Riester, Markus; Stadler, Peter F.; Klemm, Konstantin.

In: Bioinformatics, Vol. 25, No. 16, 08.2009, p. 2134-2139.

Research output: Contribution to journalArticle

Riester, M, Stadler, PF & Klemm, K 2009, 'FRANz: Reconstruction of wild multi-generation pedigrees', Bioinformatics, vol. 25, no. 16, pp. 2134-2139. https://doi.org/10.1093/bioinformatics/btp064
Riester, Markus ; Stadler, Peter F. ; Klemm, Konstantin. / FRANz : Reconstruction of wild multi-generation pedigrees. In: Bioinformatics. 2009 ; Vol. 25, No. 16. pp. 2134-2139.
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