Título:
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Data size sufficiency analyses of haplotype inference algortihms
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Autor/a:
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Cleary, Sean; St. John, Katherine; Universitat Autònoma de Barcelona. Centre de Recerca Matemàtica
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Abstract:
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We present experimental and theoretical analyses of data requirements for haplotype inference algorithms. Our experiments include a broad range of problem sizes under two standard models of tree distribution and were designed to yield statistically robust results despite the size of the sample space. Our results validate Gusfield's conjecture that a population size of n log n is required to give (with high probability) sufficient information to deduce the n haplotypes and their complete evolutionary history. The experimental results inspired our experimental finding with theoretical bounds on the population size. We also analyze the population size required to deduce some fixed fraction of the evolutionary history of a set of n haplotypes and establish linear bounds on the required sample size. These linear bounds are also shown theoretically. |
Materia(s):
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-Gens Mapatge -Filogènia Processament de dades -Inferència |
Derechos:
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open access
Aquest document està subjecte a una llicència d'ús de Creative Commons, amb la qual es permet copiar, distribuir i comunicar públicament l'obra sempre que se'n citin l'autor original, la universitat i el centre i no se'n faci cap ús comercial ni obra derivada, tal com queda estipulat en la llicència d'ús
https://creativecommons.org/licenses/by-nc-nd/2.5/ |
Tipo de documento:
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Article Prepublicació |
Editor:
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Centre de Recerca Matemàtica
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Compartir:
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Uri:
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https://ddd.uab.cat/record/44059
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