get_clustered_median_gene_expression {gtexr} | R Documentation |
Get Clustered Median Gene Expression
Description
Find median gene expression data along with hierarchical clusters.
Returns median gene expression in tissues along with The hierarchical clustering results of tissues and genes, based on gene expression, in Newick format.
Results may be filtered by dataset, gene or tissue, but at least one gene must be provided
The hierarchical clustering is performed by calculating Euclidean distances and using the average linkage method.
-
This endpoint is not paginated.
By default, this service queries the latest GTEx release.
Usage
get_clustered_median_gene_expression(
gencodeIds,
datasetId = "gtex_v8",
tissueSiteDetailIds = NULL,
.return_raw = FALSE
)
Arguments
gencodeIds |
A character vector of Versioned GENCODE IDs, e.g. c("ENSG00000132693.12", "ENSG00000203782.5"). |
datasetId |
String. Unique identifier of a dataset. Usually includes a data source and data release. Options: "gtex_v8", "gtex_snrnaseq_pilot". |
tissueSiteDetailIds |
Character vector of IDs for tissues of interest.
Can be GTEx specific IDs (e.g. "Whole_Blood"; use
|
.return_raw |
Logical. If |
Value
A tibble. Or a list if .return_raw = TRUE
.
See Also
Other Expression Data Endpoints:
get_clustered_median_exon_expression()
,
get_clustered_median_junction_expression()
,
get_clustered_median_transcript_expression()
,
get_expression_pca()
,
get_gene_expression()
,
get_median_exon_expression()
,
get_median_gene_expression()
,
get_median_junction_expression()
,
get_median_transcript_expression()
,
get_single_nucleus_gex()
,
get_single_nucleus_gex_summary()
,
get_top_expressed_genes()
Examples
## Not run:
get_clustered_median_gene_expression(gencodeIds = c(
"ENSG00000203782.5",
"ENSG00000132693.12"
))
# clustering data is stored as an attribute "clusters"
result <- get_clustered_median_gene_expression(c(
"ENSG00000203782.5",
"ENSG00000132693.12"
))
attr(result, "clusters")
# process clustering data with the ape package
# install.packages("ape")
# phylo_tree <- ape::read.tree(text = attr(result, "clusters")$tissue)
# plot(phylo_tree)
# print(phylo_tree)
## End(Not run)