fetch | R Documentation |
When you want to query just data for several genes/samples from UCSC Xena datasets, a better way
is to use these fetch_
functions instead of downloading a whole dataset. Details about functions
please see the following sections.
fetch(host, dataset) fetch_dense_values( host, dataset, identifiers = NULL, samples = NULL, check = TRUE, use_probeMap = FALSE, time_limit = 30 ) fetch_sparse_values(host, dataset, genes, samples = NULL, time_limit = 30) fetch_dataset_samples(host, dataset, limit = NULL) fetch_dataset_identifiers(host, dataset) has_probeMap(host, dataset, return_url = FALSE)
host |
a UCSC Xena host, like "https://toil.xenahubs.net".
All available hosts can be printed by |
dataset |
a UCSC Xena dataset, like "tcga_RSEM_gene_tpm".
All available datasets can be printed by running |
identifiers |
Identifiers could be probe (like "ENSG00000000419.12"),
gene (like "TP53") etc.. If it is |
samples |
ID of samples, like "TCGA-02-0047-01".
If it is |
check |
if |
use_probeMap |
if |
time_limit |
time limit for getting response in seconds. |
genes |
gene names. |
limit |
number of samples, if |
return_url |
if |
There are three primary data types: dense matrix (samples by probes (or say identifiers)), sparse (sample, position, variant), and segmented (sample, position, value).
Dense matrices can be genotypic or phenotypic, it is a sample-by-identifiers matrix. Phenotypic matrices have associated field metadata (descriptive names, codes, etc.). Genotypic matricies may have an associated probeMap, which maps probes to genomic locations. If a matrix has hugo probeMap, the probes themselves are gene names. Otherwise, a probeMap is used to map a gene location to a set of probes.
a matirx
or character vector or a list
.
fetch_dense_values
: fetches values from a dense matrix.
fetch_sparse_values
: fetches values from a sparse data.frame
.
fetch_dataset_samples
: fetches samples from a dataset
fetch_dataset_identifiers
: fetches identifies from a dataset.
has_probeMap
: checks if a dataset has ProbeMap.
library(UCSCXenaTools) host <- "https://toil.xenahubs.net" dataset <- "tcga_RSEM_gene_tpm" samples <- c("TCGA-02-0047-01", "TCGA-02-0055-01", "TCGA-02-2483-01", "TCGA-02-2485-01") probes <- c("ENSG00000282740.1", "ENSG00000000005.5", "ENSG00000000419.12") genes <- c("TP53", "RB1", "PIK3CA") # Fetch samples fetch_dataset_samples(host, dataset, 2) # Fetch identifiers fetch_dataset_identifiers(host, dataset) # Fetch expression value by probes fetch_dense_values(host, dataset, probes, samples, check = FALSE) # Fetch expression value by gene symbol (if the dataset has probeMap) has_probeMap(host, dataset) fetch_dense_values(host, dataset, genes, samples, check = FALSE, use_probeMap = TRUE)
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