There are currently three ways to find the data you need on CGC:
Please read the tutorial here.
Please read the tutorials first.
Doing a HTTP GET
on this endpoint one will get a
resource with links to all entities in the dataset. Following these
links (doing an HTTP GET
on them) one will go to a list of
entities (for example /files
) from TCGA dataset identified
with their proper URL. Further following one of these links you’ll get a
particular resource (if we went to /files
, we’ll get a
description of a particular file) with all specific properties like id,
label, etc. and links to other entities that are connected to a specific
resource (for example /cases
) that you can explore further.
From there on, the process repeats as long as you follow the links.
Create an Auth object with your token, make sure you are using the correct URL.
https://cgc-datasets-api.sbgenomics.com/
use Auth$api()
method so there is no need to type base
URL or token again.
You can issue another GET
request to the href of the
tcga object, if you want to access TCGA data.
For example, to see a list of all TCGA files, send the request:
For example, to see the metadata schema for files send the request:
Get file id from Datasets API, then use public API to copy files. Make sure your project is “TCGA” compatible, otherwise if you are trying to copy controlled access data to your non-TCGA project, you will get
"HTTP Status 403: Insufficient privileges to access the requested file."
endpoint user can filter collection resources by using a DSL in JSON format that translates as a subset of SPARQL. Main advantage here is that an end user gets the subset SPARQL expressiveness without the need to learn SPARQL specification.
body <- list(
entity = "samples",
hasCase = "0004D251-3F70-4395-B175-C94C2F5B1B81"
)
a$api(path = "query", body = body, method = "POST")
Count samples connected to a case
Issuing a GET
request to the href path will return the
following data:
Note: api
function is a light layer of httr package,
it’s different from Auth$api
call.
Suppose you want to see all cases for which the age at diagnosis is between 10 and 50. Then, you use the following query.
Note that the value of the metadata field hasAgeAtDiagnosis is a dictionary containing the keyfilter, whose value is a further dictionary with keysgt(greater than) and lt (less than) for the upper and lower bounds to filter by.
Suppose you want to see all cases that, as in the example, (Find cases with given age at diagnosis)(doc:find-all-cases-with-a-given-age-at-diagnosis), have an age at diagnosis of between 10 and 50, but that also have the disease “Kidney Chromophobe”. Then, use the following query:
body <- list(
"entity" = "cases",
"hasSample" = list(
"hasSampleType" = "Primary Tumor",
"hasPortion" = list(
"hasPortionNumber" = 11
)
),
"hasNewTumorEvent" = list(
"hasNewTumorAnatomicSite" = c("Liver", "Pancreas"),
"hasNewTumorEventType" = list(
"filter" = list(
"contains" = "Recurrence"
)
)
)
)
a$api(path = "query", body = body, method = "POST")
Issuing a GET
request to the href path
get_id <- function(obj) sapply(obj$"_embedded"$files, function(x) x$id)
names(res)
body <- list(
"entity" = "cases",
"hasSample" = list(
"hasSampleType" = "Primary Tumor",
"hasPortion" = list(
"hasPortionNumber" = 11,
"hasID" = "TCGA-DD-AAVP-01A-11"
)
),
"hasNewTumorEvent" = list(
"hasNewTumorAnatomicSite" = "Liver",
"hasNewTumorEventType" = "Intrahepatic Recurrence"
)
)
(res <- a$api(path = "files", body = body))
get_id(res)