Sentence examples for sleep trait from inspiring English sources

The 48-hr sleep recording period was partitioned into two 24-hr periods and further into a light and dark phase yielding four recording time domains per animal during which each sleep trait was computed (see Supporting Information for further details on the statistical methods).

We performed GWA analyses for the mean and environmental sensitivity of each sleep trait in the DGRP, and found many SNPs individually associated with each sleep trait, often with sex-specific effects.

Thus, only when a mutation or RNAi construct is sufficiently severe do we observe the effect on a correlated sleep trait.

Quantile-quantile (Q-Q) plots for each sleep trait show P-values deviating from the expected distribution for some of the sleep traits.

We defined our threshold P-values for each sleep trait separately by calculating the false discovery rate (FDR) using the standard Benjamini-Hochberg procedure [ 68].

We computed genetic correlations between lines for the mean value and CV E of each sleep trait to assess the extent to which the same variants affect both the mean and environmental sensitivity.

I am the lead Sleep Traits working group analyst for the TOPMed whole-genome analysis consortium, with secondary efforts in several other working groups.

Evans DS, Parimi N, Nievergelt CM, Blackwell T, Redline S, Ancoli-Israel S et al. Common genetic variants in ARNTL and NPAS2 and at chromosome 12p13 are associated with objectively measured sleep traits in the elderly.

Then, we question the adaptive value of sleep traits by using non-coding DNA as a metaphor that shows that the complexity in the design is not a definitive proof of adaptation.

Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice.

Age-matched (4 6.5 months old) male and female 5XFAD mice were monitored and compared to wild-type littermate controls for multiple sleep traits using a non-invasive, high throughput, automated piezoelectric system which detects breathing and gross body movements to characterize sleep and wake.