ICDS
Identification of Cancer Dysfunctional Subpathway with Omics Data
Identify Cancer Dysfunctional Sub-pathway 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 sub-pathways 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 sub-pathways.
- Version0.1.3
- R version≥ 4.3.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- ICDS citation info
- Last release08/01/2024
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Team
Junwei Han
Baotong Zheng
Show author detailsRolesAuthorSiyao Liu
Show author detailsRolesContributor
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- Depends1 package
- Imports5 packages
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