Sentence examples for whose imputation from inspiring English sources

Exact(1)

To filter SNPs whose imputation results had changed over time, we performed an analysis of variance test for frequency differences across batches.

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This was in contrast to the WOMAC imputation method, whose ability to impute was dependent on the rate of missing values.

A majority of those known SNPs (based on dbSNP v129) and the novel SNPs, whose positions allowed reliable functional imputation, are located in the intronic regions (CEU: ∼68%; YRI: ∼69%) (Table 1).Those intronic SNP-containing probes may, therefore, particularly affect the measurement of expression of a novel exon not present in the reference sequence.

We imputed missing values for the Health Utilities Index (about 1.4% of the sample) using regression imputation with variables whose spearman correlation coefficient with the Health Utilities Index was greater than 0.10.

Our equations for panel optimality and imputation accuracy rely on a rule that mimics computational imputation algorithms: the reference haplotype whose coalescence time with the target is minimal serves as the imputation template.

The objective of this study was to assess the accuracy of genotype imputation in Nelore cattle, using different imputation methods, different commercial and customized SNP chips and sets of animals whose genotypes were to be imputed.

M2 was the multivariate meta-analysis after mean imputation of missing coefficients, whose method was proposed in Debray et al. [ 6].

Missing A1c levels were not imputed, because patients whose physicians did not order measurement of A1c levels are likely to differ in important ways from patients whose physicians did order the test, invalidating the assumptions behind missing data imputation.

We first present a few examples of SNPs whose inference on HWE is altered by using imputation.

Then we estimate the missing values using various imputation methods and compare their performances using NRMSE which is shown below: (14) N R M S E = m e a n [ (y guess - y ans ) 2 ] s t d (y ans ) where yguess and yans are vectors whose elements are the estimated values by an imputation method and the known answers for all missing entries, respectively.

Surprisingly, typical imputation error rates (∼2%–6%) lead to a large increase in the required sample size (∼10%–60%), and in some African populations whose genotypes are particularly difficult to impute, the required sample-size increase is as high as ∼30%150%%.

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