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ICDS

Identification of Cancer Dysfunctional Subpathway with Omics Data

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About

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.

Citation ICDS citation info

Key Metrics

Version 0.1.2
R ≥ 2.10
Published 2021-07-15 1015 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Junwei Han

hanjunwei1981@163.com

Authors

Junwei Han

cre

Baotong Zheng

aut

Siyao Liu

ctb

Material

README
Reference manual
Package source

Vignettes

ICDS User Guide

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ICDS archive

Depends

R ≥ 2.10

Imports

igraph
graphite
metap
methods
org.Hs.eg.db

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knitr
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