Contrary to mean colony size, a nested ANOVA revealed significant differences among the microcosms within marker as well as a significant effect of the marker both at generation 500 (Marker: F1,10 = 9.41, p = 0.012; Microcosm: F10,24 = 2.66, p = 0.024) and generation 1000 (Marker: F1,10 = 5.67, p = 0.038; Microcosm: F10,24 = 3.21, p<0.01).
Fig. 3 Effect of the marker density on the predictability.
The effect of the marker on gene expression was analyzed in human fibroblasts, primary T cells and lymphoblastoid cell lines obtained from umbilical cords.
The effect of the marker detection algorithm is simulated by generating a number of miss detections, false measurements and, finally, adding a Gaussian noise to all measurements, according to the statistics reflected by,, and. Figure 5 Synthetic data generation process.
(3) The effect of the marker detection algorithm is simulated by generating a number of miss detections, false measurements and, finally, adding a Gaussian noise to all measurements, according to the statistics reflected by,, and. .
Associations with SNP genotype and the various phenotypes were performed using pedigree-based analysis by regressing the effect of the marker genotype while accounting for residual familial correlations among related individuals using age, sex, and body mass index (BMI) as covariates (age and BMI are positively correlated with T2DM in the AFDS).
This is a confirmation of the effect of the marker-trait association and makes these markers important candidate genes for further study.
We first evaluated the prognostic effect of the markers adjusting for the effects of age at diagnosis, gender, pT, pN, tumor grade and vascular invasion.
The main effect of the markers was denoted as M having a model involving 15 markers.
The main effect of the markers was denoted as M involving 15 markers (m).
The effect of the markers on survival probability was modelled by Proportional Hazards Model.
