## ----setup, include = FALSE---------------------------------------------- knitr::opts_chunk$set(collapse = TRUE, cache = FALSE, comment = "#>") ## ---- message = FALSE---------------------------------------------------- library(parallel) library(tidyverse) library(pathwayPCA) ## ----read_gmt------------------------------------------------------------ gmt_path <- system.file("extdata", "c2.cp.v6.0.symbols.gmt", package = "pathwayPCA", mustWork = TRUE) cp_pathwayCollection <- read_gmt(gmt_path, description = FALSE) cp_pathwayCollection ## ----read_assay---------------------------------------------------------- assay_path <- system.file("extdata", "ex_assay_subset.csv", package = "pathwayPCA", mustWork = TRUE) assay_df <- read_csv(assay_path) ## ----TransposeAssay------------------------------------------------------ assayT_df <- TransposeAssay(assay_df) assayT_df ## ----read_pinfo---------------------------------------------------------- pInfo_path <- system.file("extdata", "ex_pInfo_subset.csv", package = "pathwayPCA", mustWork = TRUE) pInfo_df <- read_csv(pInfo_path) pInfo_df ## ----innerJoin----------------------------------------------------------- exSurv_df <- inner_join(pInfo_df, assayT_df, by = "Sample") exSurv_df ## ----create_OmicsSurv_object--------------------------------------------- data("colonSurv_df") data("colon_pathwayCollection") colon_OmicsSurv <- CreateOmics( assayData_df = colonSurv_df[, -(2:3)], pathwayCollection_ls = colon_pathwayCollection, response = colonSurv_df[, 1:3], respType = "survival" ) ## ----view_Omics---------------------------------------------------------- colon_OmicsSurv ## ----accessor1----------------------------------------------------------- getAssay(colon_OmicsSurv) ## ----accessor2----------------------------------------------------------- getPathwayCollection(colon_OmicsSurv) ## ----accessor3----------------------------------------------------------- getEventTime(colon_OmicsSurv)[1:10] ## ----accessor4----------------------------------------------------------- getEvent(colon_OmicsSurv)[1:10] ## ----aespca-------------------------------------------------------------- colon_aespcOut <- AESPCA_pVals( object = colon_OmicsSurv, numReps = 0, numPCs = 2, parallel = TRUE, numCores = 2, adjustpValues = TRUE, adjustment = "BH" ) ## ----superpca------------------------------------------------------------ colon_superpcOut <- SuperPCA_pVals( object = colon_OmicsSurv, numPCs = 2, parallel = TRUE, numCores = 2, adjustpValues = TRUE, adjustment = "BH" ) ## ----viewPathwayRanks---------------------------------------------------- getPathpVals(colon_superpcOut) ## ----tidyOutput---------------------------------------------------------- colonOutGather_df <- getPathpVals(colon_superpcOut) %>% gather(variable, value, -terms) %>% mutate(score = -log(value)) %>% mutate(variable = factor(variable)) %>% mutate(variable = recode_factor(variable, rawp = "None", FDR_BH = "FDR")) graphMax <- ceiling(max(colonOutGather_df$score)) colonOutGather_df ## ----surv_spr_pval_plot, fig.height = 6, fig.width = 10.7, out.width = "100%", out.height = "60%"---- raw_df <- colonOutGather_df %>% filter(variable == "None") %>% select(-variable, -value) ggplot(raw_df) + theme_bw() + aes(x = reorder(terms, score), y = score) + geom_bar(stat = "identity", position = "dodge", fill = "#005030") + scale_fill_discrete(guide = FALSE) + ggtitle("Supervised PCA Significant Colon Pathways") + xlab("Pathways") + scale_y_continuous("Negative Log p-Value", limits = c(0, graphMax)) + geom_hline(yintercept = -log(0.01), size = 2) + coord_flip() ## ----sessionDetails------------------------------------------------------ sessionInfo()