| Title: | Aids in the Analysis of Genes Influencing Cancer Survival |
|---|---|
| Description: | Aids in the analysis of genes influencing cancer survival by including a principal function, calculator(), which calculates the P-value for each provided gene under the optimal cutoff in cancer survival studies. Grounded in methodologies from significant works, this package references Therneau's 'survival' package (Therneau, 2024; <https://CRAN.R-project.org/package=survival>) and the survival analysis extensions by Therneau and Grambsch (2000, ISBN 0-387-98784-3). It also integrates the 'survminer' package by Kassambara et al. (2021; <https://CRAN.R-project.org/package=survminer>), enhancing survival curve visualizations with 'ggplot2'. |
| Authors: | Pheonix Chen [aut, cre]
|
| Maintainer: | Pheonix Chen <[email protected]> |
| License: | Apache License 2.0 |
| Version: | 1.0.0 |
| Built: | 2024-12-23 06:29:28 UTC |
| Source: | CRAN |
By using this function, you can calculate the Pvalue of all genes you have provided.
calculator(survival, RNA, result)calculator(survival, RNA, result)
survival |
the dataframe that contains survival data |
RNA |
the dataframe that contains the expression data of genes |
result |
the dataframe which will contains the outcome |
this function will return a dataframe that contains either the gene's ensemble IDs and it's Pvalue.
library(Oncofilterfast) result <- data.frame(gene = c("A"),Pvalue = c(1)) RNA_all_path=system.file("extdata", "TCGA-LGG.htseq_fpkm.tsv", package = "Oncofilterfast") RNA_all=read.csv(RNA_all_path,header=TRUE,sep="\t") rows_to_keep <- apply(RNA_all[, -1], 1, function(row) { non_zero_count <- sum(row != 0) total_elements <- length(row) (non_zero_count / total_elements) >= 0.5 }) RNA <- RNA_all[rows_to_keep, ] survival_path=system.file("extdata", "TCGA-LGG.survival.tsv", package = "Oncofilterfast") survival=read.csv(survival_path,header=TRUE,sep="\t") final=calculator(survival=survival,RNA=RNA,result=result) print(nrow(final)) filtered_result <- final[final$Pvalue < 0.01, ] print(nrow(filtered_result)) print(filtered_result)library(Oncofilterfast) result <- data.frame(gene = c("A"),Pvalue = c(1)) RNA_all_path=system.file("extdata", "TCGA-LGG.htseq_fpkm.tsv", package = "Oncofilterfast") RNA_all=read.csv(RNA_all_path,header=TRUE,sep="\t") rows_to_keep <- apply(RNA_all[, -1], 1, function(row) { non_zero_count <- sum(row != 0) total_elements <- length(row) (non_zero_count / total_elements) >= 0.5 }) RNA <- RNA_all[rows_to_keep, ] survival_path=system.file("extdata", "TCGA-LGG.survival.tsv", package = "Oncofilterfast") survival=read.csv(survival_path,header=TRUE,sep="\t") final=calculator(survival=survival,RNA=RNA,result=result) print(nrow(final)) filtered_result <- final[final$Pvalue < 0.01, ] print(nrow(filtered_result)) print(filtered_result)