Given all these findings, we conclude: The residual analysis reveals that the error is normal distributed which suggests that the chosen model fits the data well and that the error is not introduced by the model but inherently present in the data, we achieve a correlation coefficient of r = 0.56 for R = 10 m and r = 0.83 for R = 55 m, respectively.
The residual analysis reveals that the error is normal distributed which suggests that the chosen model fits the data well and that the error is not introduced by the model but inherently present in the data, we achieve a correlation coefficient of r = 0.56 for R = 10 m and r = 0.83 for R = 55 m, respectively.
In the qPCR data we achieved a prediction accuracy of 93%.
For the HIV data, we achieved a detection limit well below this local error rate using ShoRAH alone, validating our argument.
As mentioned above, no conclusion can be drawn at this point on the occurrence of a purifying selection against m.3243A > G in the human germ line, owing to the limited number of data we achieved, all drawn from low (20%) mutant load carriers.
By combining the IR and optical data, we achieved high accurate classification.
Using Illumina MiSeq data, we achieved the annotation of all protein coding genes, as well as the genes for the two ribosomal subunits (16S and 12S) and transfer RNA genes as well.
Comparison with data we achieved for the m.8993T > G mutation (MT-ATP6 gene), responsible for the NARP/Leigh syndrome, indicates that these mutations differentially influence mtDNA segregation during oogenesis, while their impact is similar in developing somatic tissues.
For the models trained on the Mediator complex, Cohesin, coactivators and Pol II data, we achieved an AUC = 0.89, 0.79, 0.83 and 0.81, respectively (Fig. 4b).
Informants have already become patients and the data material we achieve depends on how they recall and legitimize their decision to seek care [ 18, 34].
