ICDS-package: Identification of Cancer Dysfunctional Subpathway by...
In ICDS: Identification of Cancer Dysfunctional Subpathway with Omics Data
Description
Identify Cancer Dysfunctional Subpathway by integrating gene expression, DNA methylation and copy number variation, and pathway topological information. 1)We firstly calculate the gene risk scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional subpathways within the pathways for which the discriminative scores were locally maximal. 3)Finally, the permutation test was used to calculate statistical significance level for these key dysfunctional subpathways.
ICDS documentation built on July 15, 2021, 5:06 p.m.
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Description
Identify Cancer Dysfunctional Subpathway by integrating gene expression, DNA methylation and copy number variation, and pathway topological information. 1)We firstly calculate the gene risk scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional subpathways within the pathways for which the discriminative scores were locally maximal. 3)Finally, the permutation test was used to calculate statistical significance level for these key dysfunctional subpathways.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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