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Our studies highlight the shared nature of this immunogenetic architecture across human populations, the important role of context in uncovering effects of genetic variation, and the fact that, over all tested genes, common genetic variation account for a minority of the variance in the immune transcriptome in healthy subjects.
These findings suggest that epigenetic transcriptome changes, more than genotypic variation, account for age-associated differences in sporadic breast cancer incidence and prognosis.
We arrive at nearly the same results with this model; principal components analysis shows that the first and second dimensions of variation account for 87%and7%7%, respectively, of the total variance [see Figure S3 in Additional file 1].
The larger question that still remains is how much do genes exhibiting ASE (i.e., expression variation) account for overall genetic variation in complex traits such as MD genetic resistance?
The most notable study compared DNA copy number and messenger RNA (mRNA) gene expression data in preM and postM breast cancer and concluded that transcriptomic changes, more than genotypic variation, account for age-associated differences in sporadic breast cancer incidence and prognosis [ 9].
Contribution of both sexes variation account for size differences observed, as shown in Figure 4b, because no significant changes were detected independently for each gender (males, P = 0.09, Students t test; nISF = 9, nCONTROL = 12; females, P = 0.19, Students t test; nISF = 10, nCONTROL = 12).
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The 1percentt variation accounts for the diversity in appearance -- eye, hair and skin color, for example -- and helps determine susceptibility to disease.
As computed, the structural variation accounted for approximately 50% of the total variation.
Calculated variance components indicated that small-scale variation accounted for most of the overall variability.
Similarly, from correlation perspective, around 79%% of the variation is accounted for when using occupant-based data compared to the 19%% variation accounted for by collision-based data.
Based on the mapping, we determined that V3 sequence variation accounted for neutralization resistance of approximately half the viruses tested.
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