DiffCorr - Analyzing and Visualizing Differential Correlation Networks in Biological Data
A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.
Last updated 2 months ago
7.12 score 5 stars 2 packages 29 scripts 362 downloadsTFactSR - Enrichment Approach to Predict Which Transcription Factors are Regulated
R implementation of 'TFactS' to predict which are the transcription factors (TFs), regulated in a biological condition based on lists of differentially expressed genes (DEGs) obtained from transcriptome experiments. This package is based on the 'TFactS' concept by Essaghir et al. (2010) <doi:10.1093/nar/gkq149> and expands it. It allows users to perform 'TFactS'-like enrichment approach. The package can import and use the original catalogue file from the 'TFactS' as well as users' defined catalogues of interest that are not supported by 'TFactS' (e.g., Arabidopsis).
Last updated 1 years ago
networksoftwaredifferentialexpressiongenetargetgeneexpressionmicroarrayrnaseqtranscriptionnetworkenrichment
3.70 score 3 scripts 99 downloads