survivalTCGA: Extract Survival Information From RTCGA.clinical Datasets

Description Usage Arguments Value Issues Note Author(s) See Also Examples

View source: R/survivalTCGA.R

Description

Extracts survival information from clicnial datasets from TCGA project.

Usage

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survivalTCGA(..., extract.cols = NULL, extract.names = FALSE,
  barcode.name = "patient.bcr_patient_barcode",
  event.name = "patient.vital_status",
  days.to.followup.name = "patient.days_to_last_followup",
  days.to.death.name = "patient.days_to_death")

Arguments

...

A data.frame or data.frames from TCGA study containing clinical informations. See clinical.

extract.cols

A character specifing the names of extra columns to be extracted with survival information.

extract.names

Logical, whether to extract names of passed data.frames in ....

barcode.name

A character with the name of bcr_patient_barcode which differs between TCGA releases. By default is the name from the newest release date tail(checkTCGA('Dates'),1).

event.name

A character with the name of patient.vital_status which differs between TCGA releases. By default is the name from the newest release date tail(checkTCGA('Dates'),1).

days.to.followup.name

A character with the name of patient.days_to_last_followup which differs between TCGA releases. By default is the name from the newest release date tail(checkTCGA('Dates'),1).

days.to.death.name

A character with the name of patient.days_to_death which differs between TCGA releases. By default is the name from the newest release date tail(checkTCGA('Dates'),1).

Value

A data.frame containing information about times and censoring for specific bcr_patient_barcode. The name passed in barcode.name is changed to bcr_patient_barcode.

Issues

If you have any problems, issues or think that something is missing or is not clear please post an issue on https://github.com/RTCGA/RTCGA/issues.

Note

Input data.frames should contain columns patient.bcr_patient_barcode, patient.vital_status, patient.days_to_last_followup, patient.days_to_death or theyir previous equivalents. It is recommended to use datasets from clinical.

Author(s)

Marcin Kosinski, m.p.kosinski@gmail.com

Marcin Kosinski, m.p.kosinski@gmail.com

See Also

RTCGA website http://rtcga.github.io/RTCGA/Visualizations.html.

Other RTCGA: RTCGA-package, boxplotTCGA, checkTCGA, convertTCGA, datasetsTCGA, downloadTCGA, expressionsTCGA, heatmapTCGA, infoTCGA, installTCGA, kmTCGA, mutationsTCGA, pcaTCGA, readTCGA, theme_RTCGA

Examples

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## Extracting Survival Data
library(RTCGA.clinical)
survivalTCGA(BRCA.clinical, OV.clinical, extract.cols = "admin.disease_code") -> BRCAOV.survInfo

# first munge data, then extract survival info
library(dplyr)
BRCA.clinical %>%
    filter(patient.drugs.drug.therapy_types.therapy_type %in%
               c("chemotherapy", "hormone therapy")) %>%
    rename(therapy = patient.drugs.drug.therapy_types.therapy_type) %>%
    survivalTCGA(extract.cols = c("therapy"))  -> BRCA.survInfo.chemo
                 
# first extract survival info, then munge data                  
    survivalTCGA(BRCA.clinical, 
                 extract.cols = c("patient.drugs.drug.therapy_types.therapy_type"))  %>%
    filter(patient.drugs.drug.therapy_types.therapy_type %in%
               c("chemotherapy", "hormone therapy")) %>%
    rename(therapy = patient.drugs.drug.therapy_types.therapy_type) -> BRCA.survInfo.chemo

## Kaplan-Meier Survival Curves
kmTCGA(BRCAOV.survInfo, explanatory.names = "admin.disease_code",  pval = TRUE)

kmTCGA(BRCAOV.survInfo, explanatory.names = "admin.disease_code", main = "",
       xlim = c(0,4000))
 
kmTCGA(BRCA.survInfo.chemo, explanatory.names = "therapy", xlim = c(0, 3000), conf.int = FALSE)

RTCGA documentation built on Nov. 8, 2020, 5:11 p.m.