R package hiphop: parentage assignment using bi-allelic genetic markers. Statistical software
van de Pol, M., Brouwer, L., and Cockburn, A. (2020) R package hiphop: parentage assignment using bi-allelic genetic markers. Statistical software. [Creative Work]
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Abstract
Can be used for paternity and maternity assignment and outperforms conventional methods where closely related individuals occur in the pool of possible parents. The method compares the genotypes of offspring with any combination of potentials parents and scores the number of mismatches of these individuals at bi-allelic genetic markers (e.g. Single Nucleotide Polymorphisms). It elaborates on a prior exclusion method based on the Homozygous Opposite Test (HOT; Huisman 2017 <doi:10.1111/1755-0998.12665>) by introducing the additional exclusion criterion HIPHOP (Homozygous Identical Parents, Heterozygous Offspring are Precluded; Cockburn et al., in revision). Potential parents are excluded if they have more mismatches than can be expected due to genotyping error and mutation, and thereby one can identify the true genetic parents and detect situations where one (or both) of the true parents is not sampled. Package 'hiphop' can deal with (a) the case where there is contextual information about parentage of the mother (i.e. a female has been seen to be involved in reproductive tasks such as nest building), but paternity is unknown (e.g. due to promiscuity), (b) where both parents need to be assigned, because there is no contextual information on which female laid eggs and which male fertilized them (e.g. polygynandrous mating system where multiple females and males deposit young in a common nest, or organisms with external fertilisation that breed in aggregations).
Item ID: | 69664 |
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Item Type: | Creative Work (Recorded/Rendered Work - Digital Creative Work) |
Media of Output: | R package |
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Date Deposited: | 14 Oct 2021 00:34 |
FoR Codes: | 46 INFORMATION AND COMPUTING SCIENCES > 4601 Applied computing > 460103 Applications in life sciences @ 50% 31 BIOLOGICAL SCIENCES > 3105 Genetics > 310599 Genetics not elsewhere classified @ 50% |
SEO Codes: | 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 100% |
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