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The effect of such bottlenecks depends upon the effective size of the ancestral population, its initial variation, the duration of the bottleneck, and the nature of the marker under study.
For simplicity we assume throughout the paper that the marker under study is the actual quantitative trait locus (QTL), i.e., recombination fraction θ is zero.
The relative hazards of death from SCC (and 95% CIs) associated with each marker under study were estimated by the Cox proportional hazards regression model, adjusting for the main known prognostic factors (age, sex, and TNM stage of the tumour).
The first model was an ANOVA model of the form: M i = μ + α ′ X i + e i where α were the effects of allele substitution of the marker under study, x i a column vector with the number of copies of the corresponding alleles, and e i the residual.
Recall that the background variance (i.e., the variance not due to the marker under study, the environmental measure under study, or their interaction) was simulated to consist of 30% additive polygenic genetic effects (σs2) and 70% environmental effects not-shared by the siblings (σu2).
The model, test or marker under study should first be converted to a predicted probability of the undesirable outcome (e.g. cancer on biopsy) denoted by p ^ : for a binary test, these probabilities are set to 1 and 0 for positive and negative test results; for a molecular marker, marker levels should be converted to a probability using logistic regression.
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Trimming of the whiskers decreased the level of most of the markers under study, suggesting that whiskers exert a tonic influence on plasticity markers that can be further enhanced by naturalistic use.
In both cases, 'everything else' refers to the local haplotypic background as determined by the markers under study.
If it happens that we have no evidence against the cohesion of all the markers under study (i.e. no different impossible groupings derived based on these markers), then we could start wondering what their common tree is.
For the determination of genetic parameters concerning the 332 SNP markers under study a sample of 300 accessions including 91 wild accessions as well as wine- and table- grape cultivars (Additional file 1, Table S1) was used.
However, based on the relatively small number of cases identified with KRAS-, BRAF- mutations, CIMP or MMR-deficiency, this data cannot exclude an association between MACC1 and the molecular markers under study and requires independent validation.
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