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Outliers are detected after running VIE_LSM/VIE_KALMAN by applying an outlier test (here, a simple 5- σ outlier test was used) or by manual inspection and are then removed in a second run already when reading in the data in VIE_INIT.
Assuming a normal distribution, Grubbs' outlier test can be used to remove one outlier.
We found one outlier among the control males group (Grubb's outlier test) and removed it from the analysis.
By using the Grubb's outlier test (significance level of α = 0.01), only one outlier was detected and, hence, discarded.
Let us define the outlier test function by (9).
The C test is a one-sided outlier test that will identify deviant standard deviations.
Similar(31)
Outlier loci can be neutral or non-neutral and therefore relying solely on outlier tests to characterize the selection candidacy of loci risks a resulting high rate of false positives.
The results were submitted to statistical analysis by outlier tests, normality test, homogeneity variance, analysis of variance and mean comparison, all with 95%% reliability.
Results from outlier tests are summarized in Table 3.
Grubbs' outlier tests to remove significant outliers were performed prior to the below analyses [ 48].
Using the RAD approach, outlier tests identified a total of 2413 (1.57 %) potentially selected SNPs.
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