Package: iPath 1.11.0
Kenong Su
iPath: iPath pipeline for detecting perturbed pathways at individual level
iPath is the Bioconductor package used for calculating personalized pathway score and test the association with survival outcomes. Abundant single-gene biomarkers have been identified and used in the clinics. However, hundreds of oncogenes or tumor-suppressor genes are involved during the process of tumorigenesis. We believe individual-level expression patterns of pre-defined pathways or gene sets are better biomarkers than single genes. In this study, we devised a computational method named iPath to identify prognostic biomarker pathways, one sample at a time. To test its utility, we conducted a pan-cancer analysis across 14 cancer types from The Cancer Genome Atlas and demonstrated that iPath is capable of identifying highly predictive biomarkers for clinical outcomes, including overall survival, tumor subtypes, and tumor stage classifications. We found that pathway-based biomarkers are more robust and effective than single genes.
Authors:
iPath_1.11.0.tar.gz
iPath_1.11.0.zip(r-4.5)iPath_1.11.0.zip(r-4.4)iPath_1.11.0.zip(r-4.3)
iPath_1.11.0.tgz(r-4.4-arm64)iPath_1.11.0.tgz(r-4.4-x86_64)iPath_1.11.0.tgz(r-4.3-arm64)iPath_1.11.0.tgz(r-4.3-x86_64)
iPath_1.11.0.tar.gz(r-4.5-noble)iPath_1.11.0.tar.gz(r-4.4-noble)
iPath_1.11.0.tgz(r-4.4-emscripten)iPath_1.11.0.tgz(r-4.3-emscripten)
iPath.pdf |iPath.html✨
iPath/json (API)
NEWS
| # Install 'iPath' in R: |
| install.packages('iPath', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/suke18/ipath/issues
- GSDB_example - Example gene set database
- prad_cli - Simulated clinical data for PRAD cancer patients
- prad_exprs - Expression matrix for PRAD cancer patients in TCGA
- prad_inds - Normal (0) and tumor (1) classes associated with PRAD expression data
On BioConductor:iPath-1.11.0(bioc 3.20)iPath-1.10.0(bioc 3.19)
Last updated 2 months agofrom:85b7801308
Exports:density_falliES_cal2iES_surviES_survPlotwater_fall
Dependencies:abindbackportsBHBiocParallelbootbroomcarcarDataclicodetoolscolorspacecommonmarkcorrplotcowplotcpp11curldata.tabledplyrevaluateexactRankTestsfansifarverformatRfutile.loggerfutile.optionsgenericsggplot2ggpubrggrepelggsciggsignifggtextgluegridExtragridtextgtablehighrisobandjpegkm.ciKMsurvknitrlabelinglambda.rlatticelifecyclelme4magrittrmarkdownMASSMatrixMatrixModelsmatrixStatsmaxstatmclustmgcvminqamunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpngpolynompurrrquantregR6RColorBrewerRcppRcppArmadilloRcppEigenrlangrstatixscalessnowSparseMstringistringrsurvivalsurvminersurvMisctibbletidyrtidyselectutf8vctrsviridisLitewithrxfunxml2xtableyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| density fall plot | density_fall |
| example gene set database (GSDB) | GSDB_example |
| GSEA calculation | GSEA |
| iES calculation Function | iES_cal2 |
| iES calculation Function | iES_surv |
| iES survival for a certain pathway | iES_survPlot |
| simulated clinical data for PRAD cancer patients | prad_cli |
| expression matrix for PRAD cancer patients in TCGA | prad_exprs |
| normal (0) and tumor (1) classes associated with PRAD expression data | prad_inds |
| remove genes with 0 sd | rem_data |
| set up for the parallel computing for biocParallel. | setUp_BPPARAM |
| water fall plot | water_fall |