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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/56324
Title: Efficient algorithms to identify duplicated genotypes in large datasets
Contributor(s): Ferdosi, M H  (author)orcid ; Masoodi, S (author); Khansefid, M (author)
Publication Date: 2022
Open Access: Yes
DOI: 10.3920/978-90-8686-940-4_346
Handle Link: https://hdl.handle.net/1959.11/56324
Abstract: 

In this paper, we introduced two novel algorithms to identify duplicated genotypes. The runtime of these algorithms was compared with the widely adopted Exhaustive Search algorithm using simulated data. We found that both new algorithms could significantly reduce the execution time. Further, the optimised Matrix Algebra Approach algorithm was faster than the Dis-Similarity lookup table and could improve the performance nearly 34 times compared to Exhaustive Search

Publication Type: Conference Publication
Conference Details: 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, The Netherlands, 3 – 8 July, 2022
Source of Publication: Proceedings of the 12th World Congress on Genetics Applied to Livestock Production, v.12, p. 1450-1453
Publisher: Wageningen Academic Publishers
Place of Publication: Wageningen, The Netherlands
Fields of Research (FoR) 2020: 300305 Animal reproduction and breeding
310506 Gene mapping
310509 Genomics
Socio-Economic Objective (SEO) 2020: 280101 Expanding knowledge in the agricultural, food and veterinary sciences
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Publisher/associated links: https://www.wageningenacademic.com/doi/10.3920/978-90-8686-940-4_346
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Conference Publication

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