Survival simple¶
All cancers are caused by mutations in DNA. The Cancer Genome Atlas (TCGA) is a project that begun in 2005 and aims to catalogue the mutations that cause cancer in patients. It uses highthroughput sequencing technologies and bioinformatics to achive this gaol. Beside genomic data, TCGA also records and provides detailed anonymize meta information about each patient (such as disease stage, patient age, sex, healt, etc) which are very valuable for identification of risk factors.
In this workflow, survival analysis is performed on TCGA patient survival data with BAZ2A gene mutations as predictor. The survival package is one of the most used packages for survival analysis in R.
![digraph SURV_SIMPL_workflow {
Data [group = g1; shape = invhouse, label = "Data"];
surv [shape = box; label = "Surv(pfs_days, pfs) "];
survdif [shape = box; label = "survdiff(Surv() ~ gene) "];
pchisq [shape = box; label = "p.value = \npchisq()"];
survfit [shape = box; label = "survfit() "];
summary [shape = box; label = "summary()"];
print [shape = box; label = "print() "];
Data -> surv
subgraph cluster_1 {
style = filled;
color = lightgrey;
label = "Survival package ";
node [style = filled, color = white];
surv -> survdif -> survfit;
}
survdif -> pchisq -> print;
survfit -> summary -> print;
}](../../_images/graphviz-975289a9ac451dfc179129b727460f7e1bb31ff6.png)
Simple survival analysis workflow.
Packages and Dependencies¶
There is only 1 package used in this workflow, which has no additional dependencies.
Used packages:
- CRAN: survival
Data¶
- pat.gene.rda: patient survival data from TCGA consortium processed and formatted by Phil Cheng