Air quality and meteorological datasets were explored for the period 2002 2012 through the decomposition of time-series using the Kolmogorov Zurbenko (KZ) filter.
The publicly available transcriptome datasets were explored and the expression pattern of 23 genes were analyzed using qRT-PCR in reproductive tissues.
This number of contradictions is the same with the amount of contradictions identified when the dataset was explored using ConTra.
Genetic structuring in the dataset was explored using the Bayesian clustering method STRUCTURE v2.2 [61], which can assign individuals to genetic clusters without taking into account sample origin.
Prior to developing a gene signature model, the dataset was explored as a whole – to see if there were any global differences in gene expression that might be attributed to batch effects, differences in clinical severity, or family history.
Initially, the dataset was explored by carefully designed phylogenetic analyses using PAUP 4.0 [ 68] for maximum parsimony, PHYML 3.0 [ 69] for maximum likelihood and MrBayes 3.1.2 [ 70] for Bayesian Inference of phylogeny as described in Wang et al. [ 39].
The sources of variation in the dataset were explored using cluster analysis and dominant biogeochemical processes under varying hydrologic conditions were obtained using reactive transport modeling.
This stratigraphic dataset is explored in the context of detailed bathymetry of the area based on multibeam echo sounding and surveillance and sampling of artefacts by divers.
Global gene expression changes in our dataset were explored by principal components analysis (PCA) to reveal the relationships between the different cortisol delivery regimes [33].
