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The proposed method outperformed the method of simply using the population label as a covariate in reducing false-positive rates, and it had slightly lower power.
We used population label information to estimate phased haplotype background and the following options for each chromosome: −Ku40 -Kl10 -Ki10.
The analysis was performed blinded to a population label and two groups (K = 2) were recovered (supplementary fig. S3, Supplementary Material online).
We assume that the population label for each individual is either known or has been inferred from the genotype, e.g. by using well-known programs such as Structure (Pritchard et al., 2000) or mStruct (Shringarpure and Xing, 2009).
The "isolated population" label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.
These results led us to conclude that the "isolated population" label by itself does not guarantee a greater genotyping efficiency in association studies, and that properties other than increased LD may make these populations interesting in genetic epidemiology.
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(b) The scatter plot from the DAPC which used the three population labels with the individual genotypes (n = 623 individuals).
We denote by (mathcal {P}) the set of the p̅ population labels and by (N:=sum_{alphain mathcal {P}} N_{alpha}) the total number of neurons.
The attributes in the original data set are split in two groups (see Fig. 1): those that are known for the entire population (labeled A in the figure), and those that are known only for the sample (labeled B in the figure).
A specimen of the nominate population labelled as "Baluchistan" and collected by Richard Meinertzhagen is considered of doubtful provenance.
DNA sets were stored with numbers and population labels only, at no point were numbers assigned to names from the consent forms.
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