Package: ICDS 0.1.3
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.
Authors:
ICDS_0.1.3.tar.gz
ICDS_0.1.3.zip(r-4.5)ICDS_0.1.3.zip(r-4.4)ICDS_0.1.3.zip(r-4.3)
ICDS_0.1.3.tgz(r-4.4-any)ICDS_0.1.3.tgz(r-4.3-any)
ICDS_0.1.3.tar.gz(r-4.5-noble)ICDS_0.1.3.tar.gz(r-4.4-noble)
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ICDS.pdf |ICDS.html✨
ICDS/json (API)
| # Install 'ICDS' in R: |
| install.packages('ICDS', repos = c('https://hanjunwei-lab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hanjunwei-lab/icds/issues
- envData - The variables in the environment include an example expression profile,an methylation profile,an copy number variation data,amplified genes,deleted genes,A numeric vector of z_scores,p-values,A vector of 0/1s, indicating the class of samples,interested subpathways,Optimized subpathway,and the statistical significance p value and FDR for these optimal subpathways
Last updated 4 months agofrom:599b89ae53. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
| R-4.4-win | OK | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | OK | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:combinep_threecombinep_twocoverp2zscoreFindSubPathgetCnvpGetExampleDatagetExppgetMethpopt_subpathPermutationPlotSubpathway
Dependencies:AnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64blobcachemclicodetoolscpp11crayoncurlDBIDEoptimRfastmapGenomeInfoDbGenomeInfoDbDatagluegraphgraphitehttrigraphIRangesjsonliteKEGGRESTlatticelifecyclemagrittrMASSmathjaxrMatrixMatrixModelsmemoisemetapmimemnormtmultcompmulttestmutossmvtnormnumDerivopensslorg.Hs.eg.dbpkgconfigplogrplotrixpngpurrrqqconfquantregR6rappdirsrbibutilsRcppRdpackrlangrobustbaseRSQLiteS4VectorssandwichsnSparseMsurvivalsysTFisherTH.dataUCSC.utilsvctrsXVectorzlibbioczoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Identification of Cancer Dysfunctional Subpathway by integrating DNA methylation, copy number variation, and gene expression data | ICDS-package ICDS |
| combinep_three | combinep_three |
| combinep_two | combinep_two |
| coverp2zscore | coverp2zscore |
| The variables in the environment include an example expression profile,an methylation profile,an copy number variation data,amplified genes,deleted genes,A numeric vector of z_scores,p-values,A vector of 0/1s, indicating the class of samples,interested subpathways,Optimized subpathway,and the statistical significance p value and FDR for these optimal subpathways | amp_gene cnv.p cnv_data del_gene envData exp.p exp_data label1 label2 meth.p meth_data opt_subpathways subpathdata zzz |
| FindSubPath | FindSubPath |
| getCnvp | getCnvp |
| Get the example data | GetExampleData |
| getExpp | getExpp |
| getMethp | getMethp |
| opt_subpath | opt_subpath |
| Permutation | Permutation |
| PlotSubpathway | PlotSubpathway |
