In this work, we propose the MIN-RECOMBINANT HAPLOTYPE CONFIGURATION WITH BOUNDED ERRORS problem (MRHCE), which extends the original MIN-RECOMBINANT HAPLOTYPE CONFIGURATION formulation by incorporating two common characteristics of real data: errors and missing genotypes (including untyped individuals). We describe a practical algorithm for MRHCE that is based on a reduction to the Satisfiability problem (SAT) and exploits recent advances in the constraint programming literature. An experimental analysis demonstrates the soundness of our model and the effectiveness of the algorithm under several scenarios. The analysis on real data and the comparison with state-of-the-art programs reveals that our approach couples better scalability to large and complex pedigrees with the explicit inclusion of genotyping errors into the model
Pirola, Y., DELLA VEDOVA, G., Biffani, S., Stella, A., Bonizzoni, P. (2012). A fast and practical approach to genotype phasing and imputation on a pedigree with erroneous and incomplete information. In 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2012. IEEE [10.1109/ICCABS.2012.6182643].
A fast and practical approach to genotype phasing and imputation on a pedigree with erroneous and incomplete information
PIROLA, YURI;DELLA VEDOVA, GIANLUCA;BONIZZONI, PAOLA
2012
Abstract
In this work, we propose the MIN-RECOMBINANT HAPLOTYPE CONFIGURATION WITH BOUNDED ERRORS problem (MRHCE), which extends the original MIN-RECOMBINANT HAPLOTYPE CONFIGURATION formulation by incorporating two common characteristics of real data: errors and missing genotypes (including untyped individuals). We describe a practical algorithm for MRHCE that is based on a reduction to the Satisfiability problem (SAT) and exploits recent advances in the constraint programming literature. An experimental analysis demonstrates the soundness of our model and the effectiveness of the algorithm under several scenarios. The analysis on real data and the comparison with state-of-the-art programs reveals that our approach couples better scalability to large and complex pedigrees with the explicit inclusion of genotyping errors into the modelFile | Dimensione | Formato | |
---|---|---|---|
conf-paper-12-iccabs.pdf
Solo gestori archivio
Descrizione: Articolo principale
Dimensione
255.94 kB
Formato
Adobe PDF
|
255.94 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.