TCGAbiolinks has provided a few functions to search, download and parse clinical data. This section starts by explaining the different sources for clinical information in GDC, followed by the necessary function to access these sources and it finishes by showing the insconsistencies between those sources.
In GDC database the clinical data can be retrieved from two sources:
There are two main differences:
In this example we will fetch clinical indexed data.
clinical <- GDCquery_clinic(project = "TCGA-LUAD", type = "clinical")
datatable(clinical, filter = 'top',
options = list(scrollX = TRUE, keys = TRUE, pageLength = 5),
rownames = FALSE)
In this example we will fetch clinical data directly from the clinical XML files.
query <- GDCquery(project = "TCGA-COAD",
data.category = "Clinical",
barcode = c("TCGA-RU-A8FL","TCGA-AA-3972"))
GDCdownload(query)
clinical <- GDCprepare_clinic(query, clinical.info = "patient")
datatable(clinical, options = list(scrollX = TRUE, keys = TRUE), rownames = FALSE)
clinical.drug <- GDCprepare_clinic(query, clinical.info = "drug")
datatable(clinical.drug, options = list(scrollX = TRUE, keys = TRUE), rownames = FALSE)
clinical.radiation <- GDCprepare_clinic(query, clinical.info = "radiation")
datatable(clinical.radiation, options = list(scrollX = TRUE, keys = TRUE), rownames = FALSE)
clinical.admin <- GDCprepare_clinic(query, clinical.info = "admin")
datatable(clinical.admin, options = list(scrollX = TRUE, keys = TRUE), rownames = FALSE)
Some inconsisentecies have been found in the indexed clinical data and are being investigated by the GDC team. These inconsistencies are:
# Get XML files and parse them
clin.query <- GDCquery(project = "TCGA-READ", data.category = "Clinical", barcode = "TCGA-F5-6702")
GDCdownload(clin.query)
clinical.patient <- GDCprepare_clinic(clin.query, clinical.info = "patient")
clinical.patient.followup <- GDCprepare_clinic(clin.query, clinical.info = "follow_up")
# Get indexed data
clinical.index <- GDCquery_clinic("TCGA-READ")
select(clinical.patient,vital_status,days_to_death,days_to_last_followup) %>% datatable
select(clinical.patient.followup, vital_status,days_to_death,days_to_last_followup) %>% datatable
# Vital status should be the same in the follow up table
filter(clinical.index,submitter_id == "TCGA-F5-6702") %>% select(vital_status,days_to_death,days_to_last_follow_up) %>% datatable
# Get XML files and parse them
recurrent.samples <- GDCquery(project = "TCGA-LIHC",
data.category = "Transcriptome Profiling",
data.type = "Gene Expression Quantification",
workflow.type = "HTSeq - Counts",
sample.type = "Recurrent Solid Tumor")$results[[1]] %>% select(cases)
recurrent.patients <- unique(substr(recurrent.samples$cases,1,12))
clin.query <- GDCquery(project = "TCGA-LIHC", data.category = "Clinical", barcode = recurrent.patients)
GDCdownload(clin.query)
clinical.patient <- GDCprepare_clinic(clin.query, clinical.info = "patient")
# Get indexed data
GDCquery_clinic("TCGA-LIHC") %>% filter(submitter_id %in% recurrent.patients) %>%
select(progression_or_recurrence,days_to_recurrence,tumor_grade) %>% datatable
# XML data
clinical.patient %>% select(bcr_patient_barcode,neoplasm_histologic_grade) %>% datatable