Gather Mutations for TCGA Datasets

Function gathers mutations over multiple TCGA datasets and extracts mutations and further informations about them for desired genes. See mutations.

mutationsTCGA(..., extract.cols = c("Hugo_Symbol", "Variant_Classification",
  "bcr_patient_barcode"), extract.names = TRUE, unique = TRUE)

Arguments

...

A data.frame or data.frames from TCGA study containing mutations information (RTCGA.mutations).

extract.cols

A character specifing the names of columns to be extracted with bcr_patient_barcode. If NULL all columns are returned.

extract.names

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

unique

Should the outputed data be unique. By default it's TRUE.

Note

Input data.frames should contain column bcr_patient_barcode if extract.cols is specified.

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.

See also

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

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

Examples

library(RTCGA.mutations)
library(dplyr)
mutationsTCGA(BRCA.mutations, OV.mutations) %>%
  filter(Hugo_Symbol == 'TP53') %>%
  filter(substr(bcr_patient_barcode, 14, 15) == "01") %>% # cancer tissue
  mutate(bcr_patient_barcode = substr(bcr_patient_barcode, 1, 12)) -> BRCA_OV.mutations

library(RTCGA.clinical)
survivalTCGA(BRCA.clinical, OV.clinical, extract.cols = "admin.disease_code") %>%
  rename(disease = admin.disease_code)-> BRCA_OV.clinical

BRCA_OV.clinical %>%
  left_join(BRCA_OV.mutations,
  by = "bcr_patient_barcode") %>%
  mutate(TP53 = ifelse(!is.na(Variant_Classification), "Mut",
 "WILDorNOINFO")) -> BRCA_OV.clinical_mutations

BRCA_OV.clinical_mutations %>%
  select(times, patient.vital_status, disease, TP53) -> BRCA_OV.2plot
kmTCGA(BRCA_OV.2plot, explanatory.names = c("TP53", "disease"),
       break.time.by = 400, xlim = c(0,2000))