View source: R/mutationsTCGA.R
mutationsTCGA | R Documentation |
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 )
... |
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 |
extract.names |
Logical, whether to extract names of passed data.frames in |
unique |
Should the outputed data be unique. By default it's |
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.
Input data.frames should contain column bcr_patient_barcode
if extract.cols
is specified.
Marcin Kosinski, m.p.kosinski@gmail.com
RTCGA website http://rtcga.github.io/RTCGA/articles/Visualizations.html.
Other RTCGA:
RTCGA-package
,
boxplotTCGA()
,
checkTCGA()
,
convertTCGA()
,
datasetsTCGA
,
downloadTCGA()
,
expressionsTCGA()
,
heatmapTCGA()
,
infoTCGA()
,
installTCGA()
,
kmTCGA()
,
pcaTCGA()
,
readTCGA()
,
survivalTCGA()
,
theme_RTCGA()
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))
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