Abstract
Computing maximal perfect blocks of a given panel of haplotypes is a crucial task for efficiently solving problems such as polyploid haplotype reconstruction and finding identical-by-descent segments shared among individuals of a population. Unfortunately, the presence of missing data in the haplotype panel limits the usefulness of the notion of perfect blocks.
We propose a novel algorithm for computing maximal blocks in a panel with missing data (represented as wildcards). The algorithm is based on the Positional Burrows-Wheeler Transform (PBWT) and has been implemented in the tool Wild-pBWT, available at https://github.com/AlgoLab/Wild-pBWT/. Experimental comparison showed that Wild-pBWT is 10–15 times faster than another state-of-the-art approach, while using a negligible amount of memory.
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Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 872539.
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Bonizzoni, P., Della Vedova, G., Pirola, Y., Rizzi, R., Sgrò, M. (2023). Multiallelic Maximal Perfect Haplotype Blocks with Wildcards via PBWT. In: Rojas, I., Valenzuela, O., Rojas Ruiz, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2023. Lecture Notes in Computer Science(), vol 13919. Springer, Cham. https://doi.org/10.1007/978-3-031-34953-9_5
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