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For particular traits, the estimates also may have implications for discriminating between potential models of selection and for choosing an appropriate model for linkage analysis.
Only variables significantly associated with telomere length were included in the final statistical model for linkage analysis.
Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual.
We first consider an extension of the joint model for linkage and association with conditioning on genotypes at the candidate locus (i.e. an extension to Li-cpg).
Two groundbreaking papers established budding yeast as a model for linkage analysis by dissecting the complex architecture of high temperature growth [45] and variation in the abundance of gene transcripts [46].
A fourth and final assumption of the standard HMM model for linkage analysis is that the founder's alleles at slot i do not depend on the founder's alleles at slot i − 1, hence P(x i | s i ) can be written as ∑ f P(x i | s i, f i ) P(f i ) at each slot where P(f i ) is the prior probability of the founder alleles.
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Residuals were calculated from these linear models for linkage analysis (PMD_res, DA_res, and NDA_res, respectively).
The model allows for linkage between QTL with multiple alleles and arbitrary genetic effects, including dominance, epistasis, and gametic imprinting.
Our implementation supports the factored HMM model for genetic linkage analysis with and without the state-space reduction.
These distributions are obtained by constructing a hidden Markov model for the linkage dependencies along the genome.
In a backcross model for a linkage analysis, a marker segregation type of "B/H" is used as a synonym of that of "A/H".
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