Efficient algorithms to identify duplicated genotypes in large datasets

M H Ferdosi; S Masoodi; M Khansefid

doi:10.3920/978-90-8686-940-4_346

Efficient algorithms to identify duplicated genotypes in large datasets

M H Ferdosi
, S Masoodi
, M Khansefid

Animal Genetics and Breeding Unit

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

Original language	English
Title of host publication	Proceedings of the 12th World Congress on Genetics Applied to Livestock Production
Editors	Veerkamp, R F and de Haas, Y
Place of Publication	Wageningen, The Netherlands
Publisher	Wageningen Academic Publishers
Pages	1450-1453
Volume	12
ISBN (Print)	978-90-8686-940-4
DOIs	https://doi.org/10.3920/978-90-8686-940-4_346
Publication status	Published - 31 Dec 2022
Event	12th World Congress on Genetics Applied to Livestock Production - De Doelen International Conference Center Rotterdam Schouwburgplein 50 Rotterdam, The Netherlands, Rotterdam, The Netherlands Duration: 3 Jul 2022 → 8 Jul 2022

Conference

Conference	12th World Congress on Genetics Applied to Livestock Production
City	Rotterdam, The Netherlands
Period	3/07/22 → 8/07/22

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10.3920/978-90-8686-940-4_346

https://hdl.handle.net/1959.11/56324

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title = "Efficient algorithms to identify duplicated genotypes in large datasets",

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",

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note = "12th World Congress on Genetics Applied to Livestock Production ; Conference date: 03-07-2022 Through 08-07-2022",

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Ferdosi, MH, Masoodi, S & Khansefid, M 2022, Efficient algorithms to identify duplicated genotypes in large datasets. in Veerkamp, RFAD Haas & Y (eds), Proceedings of the 12th World Congress on Genetics Applied to Livestock Production. vol. 12, 346, Wageningen Academic Publishers, Wageningen, The Netherlands, pp. 1450-1453, 12th World Congress on Genetics Applied to Livestock Production, Rotterdam, The Netherlands, 3/07/22. https://doi.org/10.3920/978-90-8686-940-4_346

Efficient algorithms to identify duplicated genotypes in large datasets. / Ferdosi, M H; Masoodi, S; Khansefid, M.
Proceedings of the 12th World Congress on Genetics Applied to Livestock Production. ed. / Veerkamp; R F and de Haas; Y. Vol. 12 Wageningen, The Netherlands: Wageningen Academic Publishers, 2022. p. 1450-1453 346.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Efficient algorithms to identify duplicated genotypes in large datasets

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