TCGAanalyze_SurvivalKM {TCGAbiolinks} | R Documentation

## survival analysis (SA) univariate with Kaplan-Meier (KM) method.

### Description

TCGAanalyze_SurvivalKM perform an univariate Kaplan-Meier (KM) survival analysis (SA). It performed Kaplan-Meier survival univariate using complete follow up with all days taking one gene a time from Genelist of gene symbols. For each gene according its level of mean expression in cancer samples, defining two thresholds for quantile expression of that gene in all samples (default ThreshTop=0.67,ThreshDown=0.33) it is possible to define a threshold of intensity of gene expression to divide the samples in 3 groups (High, intermediate, low). TCGAanalyze_SurvivalKM performs SA between High and low groups using following functions from survival package

1. survival::Surv

2. survival::survdiff

3. survival::survfit

### Usage

    TCGAanalyze_SurvivalKM(
      clinical_patient,
      dataGE,
      Genelist,
      Survresult = FALSE,
      ThreshTop = 0.67,
      ThreshDown = 0.33,
      p.cut = 0.05,
      group1,
      group2
    )

### Arguments

`clinical_patient` | is a data.frame using function 'clinic' with information related to barcode / samples such as bcr_patient_barcode, days_to_death , days_to_last_follow_up , vital_status, etc
`dataGE` | is a matrix of Gene expression (genes in rows, samples in cols) from TCGAprepare
`Genelist` | is a list of gene symbols where perform survival KM.
`Survresult` | is a parameter (default = FALSE) if is TRUE will show KM plot and results.
`ThreshTop` | is a quantile threshold to identify samples with high expression of a gene
`ThreshDown` | is a quantile threshold to identify samples with low expression of a gene
`p.cut` | p.values threshold. Default: 0.05
`group1` | a string containing the barcode list of the samples in in control group
`group2` | a string containing the barcode list of the samples in in disease group

### Value

table with survival genes pvalues from KM.

### Examples

     # Selecting only 20 genes for example
     dataBRCAcomplete <- log2(dataBRCA[1:20,] + 1)

     # clinical_patient_Cancer <- GDCquery_clinic("TCGA-BRCA","clinical")
     clinical_patient_Cancer <- data.frame(
          bcr_patient_barcode = substr(colnames(dataBRCAcomplete),1,12),
          vital_status = c(rep("alive",3),"dead",rep("alive",2),rep(c("dead","alive"),2)),
          days_to_death = c(NA,NA,NA,172,NA,NA,3472,NA,786,NA),
          days_to_last_follow_up = c(3011,965,718,NA,1914,423,NA,5,656,1417)
     )

     group1 <- TCGAquery_SampleTypes(colnames(dataBRCAcomplete), typesample = c("NT"))
     group2 <- TCGAquery_SampleTypes(colnames(dataBRCAcomplete), typesample = c("TP"))

     tabSurvKM <- TCGAanalyze_SurvivalKM(clinical_patient_Cancer,
                                         dataBRCAcomplete,
                                         Genelist = rownames(dataBRCAcomplete),
                                         Survresult = FALSE,
                                         p.cut = 0.4,
                                         ThreshTop = 0.67,
                                         ThreshDown = 0.33,
                                         group1 = group1, # Control group
                                         group2 = group2) # Disease group

     # If the groups are not specified group1 == group2 and all samples are used
     ## Not run:
     tabSurvKM <- TCGAanalyze_SurvivalKM(clinical_patient_Cancer,
                                         dataBRCAcomplete,
                                         Genelist = rownames(dataBRCAcomplete),
                                         Survresult = TRUE,
                                         p.cut = 0.2,
                                         ThreshTop = 0.67,
                                         ThreshDown = 0.33)

    ## End(Not run)

[Package TCGAbiolinks version 2.22.4 Index]