The package can identify the dysregulated canonical pathways by investigating the changes of biological relationships of pathways in the context of gene expression data. (1) The ESEA package constructs a background set of edges by extracting pathway structure (e.g. interaction, regulation, modification, and binding etc.) from the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther) and the edge sets of pathways for each of the above databases. (2) The ESEA package can can quantify the change of correlation between genes for each edge based on gene expression data with cases and controls. (3) The ESEA package uses the weighted Kolmogorov-Smirnov statistic to calculate an edge enrichment score (EES), which reflects the degree to which a given pathway is associated the specific phenotype. (4) The ESEA package can provide the visualization of the results.
|Author||Junwei Han, Xinrui Shi, Chunquan Li|
|Date of publication||2015-01-22 15:58:44|
|Maintainer||Xinrui Shi <email@example.com>|
|License||GPL (>= 2)|
calEdgeCorScore: Calculate the differential correlation score for edges
EdgesBackgrandData: The data for the background set of edges
envData: The variables in the environment variable 'envData' of the...
ESEA-internal: ESEA internal functions
ESEA.Main: Identify dysregulated pathways based on edge set enrichment...
ExampleData: The example data in the environment variable of the system
GetEdgesBackgrandData: Get the data for background set of edges
GetExampleData: Get the example data
GetPathwayEdgeData: Get the edge sets of pathways
PathwayEdgeData: The edge sets of pathways
PlotGlobEdgeCorProfile: Plot global edge correlation profile
PlotPathwayGraph: Plot the pathway-result network diagram
PlotRunEnrichment: Plot running Edge enrichment score
SavePathway2File: Save a pathway-result network to a file which can be input to...