Comprehensive pan-cancer analysis of the transcription of pre-defined gene sets at the individual level reveals novel biomarkers that links to clinical prognosis. iPath is an R package designated for the implementation of iPath algorithm, which is used to selected significiant pathways. These significant pathways demonstrate survival difference in survival for TCGA data (14 cancer types Fig.a). A schemetic overview of the glorithm is shown in (Fig.b). All the copyrights are explained by Kenong Su kenong.su@emory.edu and Prof. Zhaohui (Steve) Qin zhaohui.qin@emory.edu.
- Version 0.1.0 released
- dependent bioconductor packages: Biobase (2.42.0), qvalue(2.14.1)
- It can work on Windows, Mac and Linux platforms
library(devtools)
install_github("suke18/iPath")
R CMD INSTALL iPath_0.1.0.tar.gz # Alternatively, use this command line in the terminal.
(1). load expression data, gene set database (GSDB), and clinical data
library(iPath)
data("BRCA_exprs") # corresponding to BRCA cancer type
data("GSDB_example")
data("BRCA_cli")(2). iES score calculation per pathway per patient
iES_mat = iES_cal(BRCA_exprs, GSDB = GSDB_example)(3). iPath survival investigation
iPath_rslt = iES_surv(GSDB = GSDB_example, iES_mat = iES_mat,cli = BRCA_cli, qval=F)(4). Demonstration Figures
gs_str = "FARMER_BREAST_CANCER_APOCRINE_VS_LUMINAL"
water_fall(iES_mat = iES_mat, gs_str = gs_str)
density_fall(iES_mat = iES_mat, gs_str = gs_str)
iES_surv_one(GSDB_example, iES_mat, BRCA_cli, gs_str = gs_str)(1). waterfall plot
For a specific pathway, iPath draws the waterfall plot which contains the iES scores for tumor and normal samples. The tSNE plot of iES score for the C2 GSDB from MSigDB across these 14 cancer types is illustrated in (Fig.c).
(2). densityfall plot
For a specific pathway, iPath draws the density plots of the iES scores for tumor and normal samples. Because of the heterogeneity also wildly exists in normal samples from TCGA, iPath considers a mixture model fitting into normal samples.
(3). survival plot
After classifying tumor samples into two groups: normal-like and perturbed, iPath performs the survival anlaysis based on the two groups.
