A face centred central composite design (CCD) was used to statistically visualize the complex interactions of concentration, column length, dosage, and flow rate on the adsorption of dibenzothiophene.
Gene-expression profiles from the two data sets were compared by ranking genes measured in the two experiments according to their signed log10 p-value of differential expression between class A and class B. RRHO heat maps that graphically and statistically visualize correlations between two expression profiles were generated at http://systems.crump.ucla.edu/rankrank/ [ 23].
Since the bacterial diversity in pyrene treatments and controls in both soil-compost mixture and fertilized soil was comparably high (Additional file 1: Table S3), we evaluated in a second step whether structures in the bacterial relative abundance data can be statistically confirmed and visualized.
Therefore, only the distances which are statistically significant are visualized in this illustration.
The location of each statistically significant cluster was visualized on group-averaged midthickness and inflated cortical surfaces.
In addition, enrichment, depletion analysis and functional annotation network for GO terms were visualized and statistically evaluated using BiNGO (v2.3) [ 20] and ClueGO (v1.1) plug-ins [ 21] integrated in Cytoscape (v 2.6.3) [ 22].
Finally, a key advantage of the imaging methodologies is the 3D visualization and analysis options wherein image segmentation and analysis algorithms quantify visualized pathologies into statistically measurable parameters.
However coplots represent a qualitative way to visualize statistically significant interactions; divisions of the data into different categories are performed mathematically so that there is the same number of data points in each category of the third variable.
The proposed method is based on statistical tests supported by precise distribution theory and reliable P-values along with a technique for visualizing statistically significant islands.
We assessed these and other observations using GO-based classification of these genes to determine whether specific functional categories are statistically overrepresented, to visualize the network of functional relationships among CAGpolyQ-containing genes, and to determine whether priority candidates for polyglutamine expansion are associated with one or more specific GO terms.
