Differential Coexpressed Networks
GENERATES A DATASET CONTROLLING FOR NOISE AND GENES CONNECTED IN NETWO...
PLOT ESTIMATED CORRELATION DISTRIBUTION AFTER ADDING NOISE
PLOTS THE CORRELATIONS OF A SPECIFIC GENE
PLOT A HEATMAP REPRESENTATION OF THE DISTRIBUTION OF CORRELATIONS OF M...
RUNS A DIFCONET ANALYSIS
Estimation of DIFferential COexpressed NETworks using diverse and user metrics. This package is basically used for three functions related to the estimation of differential coexpression. First, to estimate differential coexpression where the coexpression is estimated, by default, by Spearman correlation. For this, a metric to compare two correlation distributions is needed. The package includes 6 metrics. Some of them needs a threshold. A new metric can also be specified as a user function with specific parameters (see difconet.run). The significance is be estimated by permutations. Second, to generate datasets with controlled differential correlation data. This is done by either adding noise, or adding specific correlation structure. Third, to show the results of differential correlation analyses. Please see <http://bioinformatica.mty.itesm.mx/difconet> for further information.