Dataset Information

Using Cox cluster processes to model latent pulse location patterns in hormone concentration data.

ABSTRACT: Many hormones, including stress hormones, are intermittently secreted as pulses. The pulsatile location process, describing times when pulses occur, is a regulator of the entire stress system. Characterizing the pulse location process is particularly difficult because the pulse locations are latent; only hormone concentration at sampled times is observed. In addition, for stress hormones the process may change both over the day and relative to common external stimuli. This potentially results in clustering in pulse locations across subjects. Current approaches to characterizing the pulse location process do not capture subject-to-subject clustering in locations. Here we show how a Bayesian Cox cluster process may be adapted as a model of the pulse location process. We show that this novel model of pulse locations is capable of detecting circadian rhythms in pulse locations, clustering of pulse locations between subjects, and identifying exogenous controllers of pulse events. We integrate our pulse location process into a model of hormone concentration, the observed data. A spatial birth-and-death Markov chain Monte Carlo algorithm is used for estimation. We exhibit the strengths of this model on simulated data and adrenocorticotropic and cortisol data collected to study the stress axis in depressed and non-depressed women.

SUBMITTER: Carlson NE

PROVIDER: S-EPMC5006117 | biostudies-other | 2016 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Using Cox cluster processes to model latent pulse location patterns in hormone concentration data.

Carlson Nichole E NE Grunwald Gary K GK Johnson Timothy D TD

Biostatistics (Oxford, England) 20151109 2

Many hormones, including stress hormones, are intermittently secreted as pulses. The pulsatile location process, describing times when pulses occur, is a regulator of the entire stress system. Characterizing the pulse location process is particularly difficult because the pulse locations are latent; only hormone concentration at sampled times is observed. In addition, for stress hormones the process may change both over the day and relative to common external stimuli. This potentially results in ...[more]

PMID: 26553914

Similar Datasets

Project description:BackgroundAdaptive processes shape the evolution of genomes and the diverse functions of different genomic regions are likely to have an impact on the trajectory and outcome of this evolution. The main underlying hypothesis of this study is that the evolution of Simple Sequence Repeats (SSRs) is correlated with the evolution of the genomic region in which they are located, resulting in differences of motif size, number of repeats, and levels of polymorphisms. These differences should be clearly detectable when analyzing the frequency and type of SSRs within the genome of a species, when studying populations within a species, and when comparing closely related sister taxa. By coupling a genome-wide SSR survey in the genome of the plant pathogenic fungus Heterobasidion irregulare with an analysis of intra- and interspecific variability of 39 SSR markers in five populations of the two sibling species H. irregulare and H. annosum, we investigated mechanisms of evolution of SSRs.ResultsResults showed a clear dominance of trirepeats and a selection against other repeat number, i.e. di- and tetranucleotides, both in regions inside Open Reading Frames (ORFs) and upstream 5' untranslated region (5'UTR). Locus per locus AMOVA showed SSRs both inside ORFs and upstream 5'UTR were more conserved within species compared to SSRs in other genomic regions, suggesting their evolution is constrained by the functions of the regions they are in. Principal coordinates analysis (PCoA) indicated that even if SSRs inside ORFs were less polymorphic than those in intergenic regions, they were more powerful in differentiating species. These findings indicate SSRs evolution undergoes a directional selection pressure comparable to that of the ORFs they interrupt and to that of regions involved in regulatory functions.ConclusionsOur work linked the variation and the type of SSRs with regions upstream 5'UTR, putatively harbouring regulatory elements, and shows that the evolution of SSRs might be affected by their location in the genome. Additionally, this study provides a first glimpse on a possible molecular basis for fast adaptation to the environment mediated by SSRs.

Dataset Information

Using Cox cluster processes to model latent pulse location patterns in hormone concentration data.

Publications

Using Cox cluster processes to model latent pulse location patterns in hormone concentration data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets