Data Analysis
The GDC data analysis endpoints allow API users to programmatically explore data in the GDC using advanced filters at a gene and mutation level. Survival analysis data is also available.
Endpoints
The following data analysis endpoints are available from the GDC API:
| Node | Endpoint | Description |
|---|---|---|
| Genes | /genes | Allows users to access summary information about each gene using its Ensembl ID. |
| Gene Expression | /gene_expression/availability | Allows users to retrieve the availability of gene expression data for specific cases and/or genes. |
| /gene_expression/values | Get gene expression values for specified cases and genes. | |
| /gene_expression/gene_selection | Select the most variably expressed genes for a collection of cases and genes. | |
| SSMS | /ssms | Allows users to access information about each somatic mutation. For example, a ssm would represent the transition of C to T at position 52000 of chromosome 1. |
/ssms/<ssm_id> |
Get information about a specific ssm using a <ssm_id>, often supplemented with the expand option to show fields of interest. |
|
| /ssm_occurrences | A ssm entity as applied to a single instance (case). An example of a ssm occurrence would be that the transition of C to T at position 52000 of chromosome 1 occurred in patient TCGA-XX-XXXX. |
|
/ssm_occurrences/<ssm_occurrences_id> |
Get information about a specific ssm occurrence using a <ssm_occurrences_id>, often supplemented with the expand option to show fields of interest. |
|
| CNVS | /cnvs | Allows users to access data about copy number variations (cnvs). This data will be specifc to cnvs and not a specific case. |
/cnvs/<cnv_id> |
Get information about a specific copy number variation using a <cnv_id>, often supplemented with the expand option to show fields of interest. |
|
| /cnvs/ids | This endpoint will retrieve nodes that contain the queried cnv_id. This is accomplished by adding the query parameter: /cnvs/ids?query=<cnv_id>. |
|
| /cnv_occurrences | A cnv entity as applied to a single case. |
|
/cnv_occurrences/<cnv_occurrence_id> |
Get information about a specific copy number variation occurrence using a <cnv_occurrence_id>, often supplemented with the expand option to show fields of interest. |
|
| /cnv_occurrences/ids | This endpoint will retrieve nodes that contain the queried cnv_occurrence_id. This is accomplished by adding the query parameter: /cnv_occurrences/ids?query=<cnv_occurrences_id> |
|
| scRNA-Seq Gene Expression | /scrna_seq/gene_expression | Returns scRNA-Seq gene expression data for specific cases or files, with details about gene expression across different cell IDs. |
| Analysis | /analysis/top_cases_counts_by_genes | Returns the number of cases with a mutation in each gene listed in the gene_ids parameter for each project. Note that this endpoint cannot be used with the format or fields parameters. |
| /analysis/top_mutated_genes_by_project | Returns a list of genes that have the most mutations within a given project. | |
| /analysis/top_mutated_cases_by_gene | Generates information about the cases that are most affected by mutations in a given number of genes | |
| /analysis/mutated_cases_count_by_project | Returns counts for the number of cases that have associated ssm data in each project. The number of affected cases can be found under "case_with_ssm": {"doc_count": $case_count}. |
|
| /analysis/survival | Survival plots can be generated in the Data Portal for different subsets of data, based upon many query factors such as variants, disease type and projects. This endpoint can be used to programmatically retrieve the raw data to generate these plots and apply different filters to the data. (see Survival Example) |
The methods for retrieving information from these endpoints are very similar to those used for the cases and files endpoints. These methods are explored in depth in the API Search and Retrieval documentation. The _mapping parameter can also be used with each of these endpoints to generate a list of potential fields. For example:
https://api.gdc.cancer.gov/ssms/_mapping
While it is not an endpoint, the observation entity is featured in the visualization section of the API. The observation entity provides information from the MAF file, such as read depth and normal genotype, that supports the validity of the associated ssm. An example is demonstrated below:
curl "https://api.gdc.cancer.gov/ssms/57bb3f2e-ec05-52c2-ab02-7065b7d24849?expand=occurrence.case.observation.read_depth&pretty=true"
{
"data": {
"ncbi_build": "GRCh38",
"occurrence": [
{
"case": {
"observation": [
{
"read_depth": {
"t_ref_count": 321,
"t_alt_count": 14,
"t_depth": 335,
"n_depth": 115
}
}
]
}
}
],
"tumor_allele": "G",
"mutation_type": "Simple Somatic Mutation",
"end_position": 14304578,
"reference_allele": "C",
"ssm_id": "57bb3f2e-ec05-52c2-ab02-7065b7d24849",
"start_position": 14304578,
"mutation_subtype": "Single base substitution",
"cosmic_id": null,
"genomic_dna_change": "chr5:g.14304578C>G",
"gene_aa_change": [
"TRIO L229V",
"TRIO L437V",
"TRIO L447V",
"TRIO L496V"
],
"chromosome": "chr5"
},
"warnings": {}
}
Genes Endpoint Examples
Example 1: A user would like to access information about the gene ZMPSTE24, which has an Ensembl gene ID of ENSG00000084073. This would be accomplished by appending ENSG00000084073 (gene_id) to the genes endpoint.
curl "https://api.gdc.cancer.gov/genes/ENSG00000084073?pretty=true"
{
"data": {
"canonical_transcript_length": 3108,
"description": "This gene encodes a member of the peptidase M48A family. The encoded protein is a zinc metalloproteinase involved in the two step post-translational proteolytic cleavage of carboxy terminal residues of farnesylated prelamin A to form mature lamin A. Mutations in this gene have been associated with mandibuloacral dysplasia and restrictive dermopathy. [provided by RefSeq, Jul 2008]",
"cytoband": [
"1p34.2"
],
"gene_start": 40258107,
"canonical_transcript_length_genomic": 36078,
"gene_id": "ENSG00000084073",
"gene_strand": 1,
"canonical_transcript_length_cds": 1425,
"gene_chromosome": "1",
"synonyms": [
"FACE-1",
"HGPS",
"PRO1",
"STE24",
"Ste24p"
],
"is_cancer_gene_census": null,
"biotype": "protein_coding",
"gene_end": 40294184,
"canonical_transcript_id": "ENST00000372759",
"symbol": "ZMPSTE24",
"name": "zinc metallopeptidase STE24"
},
"warnings": {}
}
Example 2: A user wants a subset of elements such as a list of coordinates for all genes on chromosome 7. The query can be filtered for only results from chromosome 7 using a JSON-formatted query that is URL-encoded.
curl "https://api.gdc.cancer.gov/genes?pretty=true&fields=gene_id,symbol,gene_start,gene_end&format=tsv&size=2000&filters=%7B%0D%0A%22op%22%3A%22in%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22gene_chromosome%22%2C%0D%0A%22value%22%3A%5B%0D%0A%227%22%0D%0A%5D%0D%0A%7D%0D%0A%7D"
gene_start gene_end symbol id
28995231 29195451 CPVL ENSG00000106066
33014114 33062797 NT5C3A ENSG00000122643
143052320 143053347 OR6V1 ENSG00000225781
100400826 100428992 ZCWPW1 ENSG00000078487
73861159 73865893 WBSCR28 ENSG00000175877
64862999 64864370 EEF1DP4 ENSG00000213640
159231435 159233377 PIP5K1P2 ENSG00000229435
141972631 141973773 TAS2R38 ENSG00000257138
16646131 16706523 BZW2 ENSG00000136261
149239651 149255609 ZNF212 ENSG00000170260
57405025 57405090 MIR3147 ENSG00000266168
130393771 130442433 CEP41 ENSG00000106477
150800403 150805120 TMEM176A ENSG00000002933
93591573 93911265 GNGT1 ENSG00000127928
117465784 117715971 CFTR ENSG00000001626
5879827 5886362 OCM ENSG00000122543
144118461 144119360 OR2A15P ENSG00000239981
30424527 30478784 NOD1 ENSG00000106100
137227341 137343865 PTN ENSG00000105894
84876554 84876956 HMGN2P11 ENSG00000232605
107470018 107475659 GPR22 ENSG00000172209
31330711 31330896 RP11-463M14.1 ENSG00000271027
78017057 79453574 MAGI2 ENSG00000187391
55736779 55739605 CICP11 ENSG00000237799
142111749 142222324 RP11-1220K2.2 ENSG00000257743
(truncated)
Gene Expression Examples
Gene Expression Availability Endpoint
The purpose of this endpoint is to retrieve the availability of gene expression data for cases, genes, or both. The availability response informs the user if gene expression data exists for each case or gene, which are specified with case and gene IDs. Gene expression data is only available for protein-coding genes.
Example 1: A user wants to get the availability of gene expression data for a set of cases and genes.
{
"case_ids": [
"6d4f38db-a97b-4dc0-8dc5-2ac7f2cc5e38",
"e3b32485-b204-43a7-93a5-601408fcdf96"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
]
}
curl -X 'POST' \
'https://api.gdc.cancer.gov/gene_expression/availability' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"case_ids": [
"6d4f38db-a97b-4dc0-8dc5-2ac7f2cc5e38",
"e3b32485-b204-43a7-93a5-601408fcdf96"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
]
}'
{
"cases": {
"details": [
{
"case_id": "6d4f38db-a97b-4dc0-8dc5-2ac7f2cc5e38",
"has_gene_expression_values": false
},
{
"case_id": "e3b32485-b204-43a7-93a5-601408fcdf96",
"has_gene_expression_values": true
}
],
"with_gene_expression_count": 1,
"without_gene_expression_count": 1
},
"genes": {
"details": [
{
"gene_id": "ENSG00000141510",
"has_gene_expression_values": true
},
{
"gene_id": "ENSG00000181143",
"has_gene_expression_values": true
}
],
"with_gene_expression_count": 2,
"without_gene_expression_count": 0
}
}
Gene Expression Values Endpoint
The purpose of this endpoint is to retrieve the gene expression values for the given cases and genes. The response is a TSV containing the expression values for genes to cases.
The tsv_units of gene expression data must be defined by exactly one of the following:
uqfpkm- FPKM-UQ values. More information on calculations can be found here.median_centered_log2_uqfpkm- Median-centered log2(FPKM-UQ+1) values.
The median_centered_log2_uqfpkm is calculated through the following steps:
- Calculate the Median: Determine the median of all provided log2(uqfpkm + 1) values.
- Compute Median-Centered Values: Subtract the median from each log2(uqfpkm + 1) value.
- Generate the Result Sequence: Create a new sequence with the median-centered values, preserving the original order.
Example 1: A user wants to get expression values using case IDs and gene IDs.
{
"case_ids": [
"6d4f38db-a97b-4dc0-8dc5-2ac7f2cc5e38",
"e3b32485-b204-43a7-93a5-601408fcdf96",
"000ead0d-abf5-4606-be04-1ea31b999840",
"001ab32d-f924-4753-ad67-4366fb845ae6"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
],
"tsv_units": "median_centered_log2_uqfpkm",
"format": "tsv"
}
curl -X 'POST' \
'https://api.gdc.cancer.gov/gene_expression/values' \
-H 'accept: text/tab-separated-values' \
-H 'Content-Type: application/json' \
-d '{
"case_ids": [
"6d4f38db-a97b-4dc0-8dc5-2ac7f2cc5e38",
"e3b32485-b204-43a7-93a5-601408fcdf96",
"000ead0d-abf5-4606-be04-1ea31b999840",
"001ab32d-f924-4753-ad67-4366fb845ae6"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
],
"tsv_units": "median_centered_log2_uqfpkm",
"format": "tsv"
}'
gene_id 000ead0d-abf5-4606-be04-1ea31b999840 001ab32d-f924-4753-ad67-4366fb845ae6 e3b32485-b204-43a7-93a5-601408fcdf96
ENSG00000141510 -0.58248 1.75830 0.00000
ENSG00000181143 -0.02529 0.00000 3.52293
Gene Expression Gene Selection Endpoint
Select the most variably expressed genes for a collection of cases and collection of genes. The request must define a collection of cases, a collection of genes, and a selection size. A minimum expression value may optionally be defined.
A collection of cases must be defined by case IDs.
A collection of genes must be defined by exactly one of the following:
gene_idsgene_typewhich has only one value:protein_coding.
A selection size (selection_size) defines the maximum number of genes to select.
An optional threshold (min_median_log2_uqfpkm) defines a minimum value for expression. Defaults to 1.
Example 1: A user wants to get the most variably expressed genes for a list of case UUIDs and a list of Ensembl gene IDs.
{
"case_ids": [
"000ead0d-abf5-4606-be04-1ea31b999840",
"001ab32d-f924-4753-ad67-4366fb845ae6",
"0024c94c-88ff-49d9-8dc4-bf77f832d85e",
"003f4f85-3244-4132-8c9d-c29f09382269",
"005d0639-c923-470f-a179-02a4dbb5cdf2",
"006931bb-f5b1-4aa4-b0a8-af517a912db0",
"0084e8b6-57fc-48b6-aa77-fec6e45161d2",
"008d3744-e7f0-41a5-a419-702960cf1ccb",
"0094e07c-1595-402e-9d38-68b9cac71e7b",
"00bd58bd-223d-433e-b60a-5bf355f342b1"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
],
"selection_size": 1
}
curl -X 'POST' \
'https://api.gdc.cancer.gov/gene_expression/gene_selection' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"case_ids": [
"000ead0d-abf5-4606-be04-1ea31b999840",
"001ab32d-f924-4753-ad67-4366fb845ae6",
"0024c94c-88ff-49d9-8dc4-bf77f832d85e",
"003f4f85-3244-4132-8c9d-c29f09382269",
"005d0639-c923-470f-a179-02a4dbb5cdf2",
"006931bb-f5b1-4aa4-b0a8-af517a912db0",
"0084e8b6-57fc-48b6-aa77-fec6e45161d2",
"008d3744-e7f0-41a5-a419-702960cf1ccb",
"0094e07c-1595-402e-9d38-68b9cac71e7b",
"00bd58bd-223d-433e-b60a-5bf355f342b1"
],
"gene_ids": [
"ENSG00000141510",
"ENSG00000181143"
],
"selection_size": 1
}'
{
"gene_selection": [
{
"log2_uqfpkm_stddev": 0.9962971125913709,
"log2_uqfpkm_median": 2.904457107848132,
"gene_id": "ENSG00000141510",
"symbol": "TP53"
}
]
}
Simple Somatic Mutation Endpoint Examples
Example 1: Similar to the /genes endpoint, a user would like to retrieve information about the mutation based on its COSMIC ID. This would be accomplished by creating a JSON filter, which will then be encoded to URL for the curl command.
{
"op":"in",
"content":{
"field":"cosmic_id",
"value":[
"COSM1135366"
]
}
}
curl 'https://api.gdc.cancer.gov/ssms?pretty=true&filters=%7B%0A%22op%22%3A%22in%22%2C%0A%22content%22%3A%7B%0A%22field%22%3A%22cosmic_id%22%2C%0A%2value%22%3A%5B%0A%22COSM1135366%22%0A%5D%0A%7D%0A%7D%0A'
{
"data": {
"hits": [
{
"id": "edd1ae2c-3ca9-52bd-a124-b09ed304fcc2",
"start_position": 25245350,
"gene_aa_change": [
"KRAS G12D"
],
"reference_allele": "C",
"ncbi_build": "GRCh38",
"cosmic_id": [
"COSM1135366",
"COSM521"
],
"mutation_subtype": "Single base substitution",
"mutation_type": "Simple Somatic Mutation",
"chromosome": "chr12",
"ssm_id": "edd1ae2c-3ca9-52bd-a124-b09ed304fcc2",
"genomic_dna_change": "chr12:g.25245350C>T",
"tumor_allele": "T",
"end_position": 25245350
}
],
"pagination": {
"count": 1,
"total": 1,
"size": 10,
"from": 0,
"sort": "",
"page": 1,
"pages": 1
}
},
"warnings": {}
}
Example 2: Based on the previous example's ssm_id (8b3c1a7a-e4e0-5200-9d46-5767c2982145), a user would like to look at the consequences and the VEP impact due to this ssm.
curl 'https://api.gdc.cancer.gov/ssms/edd1ae2c-3ca9-52bd-a124-b09ed304fcc2?pretty=true&expand=consequence.transcript&fields=consequence.transcript.annotation.vep_impact'
{
"data": {
"consequence": [
{
"transcript": {
"annotation": {
"vep_impact": "MODERATE"
},
"transcript_id": "ENST00000557334",
"aa_end": 12,
"consequence_type": "missense_variant",
"aa_start": 12,
"is_canonical": false,
"aa_change": "G12D",
"ref_seq_accession": ""
}
},
{
"transcript": {
"annotation": {
"vep_impact": "MODERATE"
},
"transcript_id": "ENST00000256078",
"aa_end": 12,
"consequence_type": "missense_variant",
"aa_start": 12,
"is_canonical": true,
"aa_change": "G12D",
"ref_seq_accession": "NM_001369786.1&NM_033360.4"
}
},
{
"transcript": {
"annotation": {
"vep_impact": "MODERATE"
},
"transcript_id": "ENST00000311936",
"aa_end": 12,
"consequence_type": "missense_variant",
"aa_start": 12,
"is_canonical": false,
"aa_change": "G12D",
"ref_seq_accession": "NM_001369787.1&NM_004985.5"
}
},
{
"transcript": {
"annotation": {
"vep_impact": "MODERATE"
},
"transcript_id": "ENST00000556131",
"aa_end": 12,
"consequence_type": "missense_variant",
"aa_start": 12,
"is_canonical": false,
"aa_change": "G12D",
"ref_seq_accession": ""
}
}
]
},
"warnings": {}
}
Simple Somatic Mutation Occurrence Endpoint Examples
Example 1: A user wants to determine the chromosome in case TCGA-DU-6407 that contains the greatest number of ssms. As this relates to mutations that are observed in a case, the ssm_occurrences endpoint is used.
{
"op":"in",
"content":{
"field":"case.submitter_id",
"value":["TCGA-DU-6407"]
}
}
curl "https://api.gdc.cancer.gov/ssm_occurrences?format=tsv&fields=ssm.chromosome&size=5000&filters=%7B%0D%0A%22op%22%3A%22in%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22case.submitter_id%22%2C%0D%0A%22value%22%3A%5B%0D%0A%22TCGA-DU-6407%22%0D%0A%5D%0D%0A%7D%0D%0A%7D"
id ssm.chromosome
105e7811-4601-5ccb-ae93-e7107923599e chr16
faee73a9-4804-58ea-a91f-18c3d901774f chr2
99b3aad4-d368-506d-99d6-047cbe5dff0f chr2
2cb06277-993e-5502-b2c5-263037c45d18 chr10
f08dcc53-eadc-5ceb-bf31-f6b38629e4cb chr19
97c5b38b-fc96-57f5-8517-cc702b3aa70a chr6
19ca262d-b354-54a0-b582-c4719e37e91d chrX
b4822fc9-f0cc-56fd-9d97-f916234e309d chr2
22a07c7c-16ba-51df-a9a9-1e41e2a45225 chrX
0010a89d-9434-5d97-8672-36ee394767d0 chr17
3a023e72-da92-54f7-aa18-502c1076b2b0 chr5
391011ff-c1fd-5e2a-a128-652bc660f64c chr10
3548ecfe-5186-51e7-8f40-37f4654cd260 chr2
b67f31b5-0341-518e-8fcc-811cd2e36af1 chr3
4a93d7a5-988d-5055-80da-999dc3b45d80 chr1
9dc3f7cd-9efa-530a-8524-30d067e49d54 chr13
552c09d1-69b1-5c04-b543-524a6feae3eb chr3
dbc5eafa-ea26-5f1c-946c-b6974a345b69 chr12
d25129ad-3ad7-584f-bdeb-fba5c3881d32 chr17
1378cbc4-af88-55bb-b2e5-185bb4246d7a chr10
c44a93a1-5c73-5cff-b40e-98ce7e5fe57b chr19
1267330b-ae6d-5e25-b19e-34e98523679e chr21
1476a543-2951-5ec4-b165-67551b47d810 chr17
727c9d57-7b74-556f-aa5b-e1ca1f76d119 chr10
94abd5fd-d539-5a4a-8719-9615cf7cec5d chr1
a76469cb-973c-5d4d-bf82-7cf4e8f6c129 chr17
Example 2: A user has retrieved a ssm_occurrence, and would like to determine if that case also has diagnostic information.
curl 'https://api.gdc.cancer.gov/ssm_occurrences/6fd8527d-5c40-5604-8fa9-0ce798eec231?pretty=true&expand=case.diagnoses'
{
"data": {
"ssm_occurrence_id": "6fd8527d-5c40-5604-8fa9-0ce798eec231",
"case": {
"diagnoses": [
{
"ajcc_pathologic_t": "T3b",
"synchronous_malignancy": "No",
"morphology": "8720/3",
"ajcc_pathologic_stage": "Stage IIB",
"ajcc_pathologic_n": "N0",
"ajcc_pathologic_m": "M0",
"submitter_id": "TCGA-Z2-A8RT_diagnosis",
"days_to_diagnosis": 0,
"last_known_disease_status": "not reported",
"tissue_or_organ_of_origin": "Skin, NOS",
"days_to_last_follow_up": 839.0,
"age_at_diagnosis": 15342,
"primary_diagnosis": "Malignant melanoma, NOS",
"classification_of_tumor": "not reported",
"prior_malignancy": "no",
"year_of_diagnosis": 2012,
"diagnosis_id": "1d06a202-c51a-52e2-805f-eeb5f7fac14e",
"icd_10_code": "C44.6",
"site_of_resection_or_biopsy": "Skin of upper limb and shoulder",
"prior_treatment": "No",
"state": "released",
"tumor_grade": "Not Reported",
"progression_or_recurrence": "not reported",
"ajcc_staging_system_edition": "7th"
}
]
}
},
"warnings": {}
}
Copy Number Variation Endpoint Examples
Example 1: A user is interested in finding the first 30 cnvs found on chromosome 4 that have a cnv loss.
{
"op": "and",
"content": [
{
"op": "in",
"content": {
"field": "chromosome",
"value": [
"4"
]
}
},
{
"op": "in",
"content": {
"field": "cnv_change",
"value": [
"Loss"
]
}
}
]
}
curl 'https://api.gdc.cancer.gov/cnvs?filters=%7B%0D%0A+++%22op%22%3A+%22and%22%2C%0D%0A++++%22content%22%3A+%5B%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22chromosome%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%224%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv_change%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Loss%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%0D%0A++++%5D%0D%0A%7D&size=30&sort=start_position&format=tsv'
chromosome cnv_change cnv_change_5_category cnv_id end_position gene_level_cn id ncbi_build start_position
4 Loss Loss 11381600-f064-5c42-90d2-a5c79c8b23e1 88208 True 11381600-f064-5c42-90d2-a5c79c8b23e1 GRCh38 53286
4 Loss Homozygous Deletion 8884174a-1a74-5fec-af2a-1abd816c4022 88208 True 8884174a-1a74-5fec-af2a-1abd816c4022 GRCh38 53286
4 Loss Homozygous Deletion 1dc3143b-99d8-5d9b-80a4-84a4e8967b37 202303 True 1dc3143b-99d8-5d9b-80a4-84a4e8967b37 GRCh38 124501
4 Loss Loss edef0f2f-c1a7-507c-842f-e1f8a568df9d 202303 True edef0f2f-c1a7-507c-842f-e1f8a568df9d GRCh38 124501
4 Loss Loss eba92f9a-b045-54a8-948a-451e439ed418 305474 True eba92f9a-b045-54a8-948a-451e439ed418 GRCh38 270675
4 Loss Homozygous Deletion 1d656e18-64c3-51c1-856f-eba2a2bb4214 305474 True 1d656e18-64c3-51c1-856f-eba2a2bb4214 GRCh38 270675
4 Loss Loss 89319453-2a3f-5ebe-be30-8af0426e0343 384868 True 89319453-2a3f-5ebe-be30-8af0426e0343 GRCh38 337814
4 Loss Homozygous Deletion a392d072-2650-5c7f-b3a6-d325680d87fb 384868 True a392d072-2650-5c7f-b3a6-d325680d87fb GRCh38 337814
4 Loss Homozygous Deletion 653d70d7-07fa-5b5a-8961-ba031060e33a 499156 True 653d70d7-07fa-5b5a-8961-ba031060e33a GRCh38 425815
4 Loss Loss 6567929c-4b6f-582b-aedf-acde2c0ec736 499156 True 6567929c-4b6f-582b-aedf-acde2c0ec736 GRCh38 425815
4 Loss Loss 2daff58b-5065-50cd-8239-253180eaee81 540200 True 2daff58b-5065-50cd-8239-253180eaee81 GRCh38 499210
4 Loss Homozygous Deletion a793c3d6-805b-531e-86fc-0b92eb3b8d98 540200 True a793c3d6-805b-531e-86fc-0b92eb3b8d98 GRCh38 499210
4 Loss Loss 2b42c8d4-6d85-5352-96e1-9e52e722c248 576295 True 2b42c8d4-6d85-5352-96e1-9e52e722c248 GRCh38 573880
4 Loss Homozygous Deletion 6a7256cb-f674-58e1-8359-13045f0e5abc 576295 True 6a7256cb-f674-58e1-8359-13045f0e5abc GRCh38 573880
4 Loss Homozygous Deletion a055b2b3-8135-509c-b870-ef7ab693d394 670782 True a055b2b3-8135-509c-b870-ef7ab693d394 GRCh38 625573
4 Loss Loss 2646cdc7-7602-59a4-ae4f-d171352bae88 670782 True 2646cdc7-7602-59a4-ae4f-d171352bae88 GRCh38 625573
4 Loss Loss c11ad392-949f-593f-a3ab-d834b2f82809 674330 True c11ad392-949f-593f-a3ab-d834b2f82809 GRCh38 672436
4 Loss Homozygous Deletion b98c4b26-6c62-5a89-931a-bba7f882083e 674330 True b98c4b26-6c62-5a89-931a-bba7f882083e GRCh38 672436
4 Loss Loss f31be658-4de0-549e-81be-e79759879acf 682033 True f31be658-4de0-549e-81be-e79759879acf GRCh38 673580
4 Loss Homozygous Deletion efb72922-c8ee-51bd-9340-b6c24cf0e120 682033 True efb72922-c8ee-51bd-9340-b6c24cf0e120 GRCh38 673580
4 Loss Homozygous Deletion f7e8f2a0-50ba-57b7-9604-109de3832a0d 689271 True f7e8f2a0-50ba-57b7-9604-109de3832a0d GRCh38 681829
4 Loss Loss d72c62f2-fc29-5b83-9839-7f6b03970aff 689271 True d72c62f2-fc29-5b83-9839-7f6b03970aff GRCh38 681829
4 Loss Loss 45448d47-6e13-5d30-824d-96150a7f55c6 770640 True 45448d47-6e13-5d30-824d-96150a7f55c6 GRCh38 705748
4 Loss Homozygous Deletion 8f439ea0-b792-5d31-a457-f01ead7351d4 770640 True 8f439ea0-b792-5d31-a457-f01ead7351d4 GRCh38 705748
4 Loss Loss 517e65ea-9084-54c2-abe0-b1b47e9f872c 826129 True 517e65ea-9084-54c2-abe0-b1b47e9f872c GRCh38 784957
4 Loss Homozygous Deletion c73f54a7-6c75-51c8-b9ee-9a0f9e649eca 826129 True c73f54a7-6c75-51c8-b9ee-9a0f9e649eca GRCh38 784957
4 Loss Homozygous Deletion f7fa174c-2c9b-5462-b807-a1f6d18b1320 932373 True f7fa174c-2c9b-5462-b807-a1f6d18b1320 GRCh38 849276
4 Loss Loss b5a09c9b-d842-5b76-a500-56f18252c29d 932373 True b5a09c9b-d842-5b76-a500-56f18252c29d GRCh38 849276
4 Loss Homozygous Deletion 3b7a64d1-f4d2-5186-ba74-07483d5f53c1 958656 True 3b7a64d1-f4d2-5186-ba74-07483d5f53c1 GRCh38 932387
4 Loss Loss e3a3b61d-2881-5ad4-90bf-58ef29ae9ecb 958656 True e3a3b61d-2881-5ad4-90bf-58ef29ae9ecb GRCh38 932387
Example 2: A user is interested in finding the first 30 cnvs found on chromosome 4 that have cnv homozygous deletions only.
{
"op": "and",
"content": [
{
"op": "in",
"content": {
"field": "chromosome",
"value": [
"4"
]
}
},
{
"op": "in",
"content": {
"field": "cnv_change_5_category",
"value": [
"Homozygous Deletion"
]
}
}
]
}
curl 'https://api.gdc.cancer.gov/cnvs?filters=%7B%0A%20%20%20%20%20%20%20%20%22op%22%3A%20%22and%22%2C%0A%20%20%20%20%20%20%20%20%22content%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22chromosome%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%224%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22cnv_change_5_category%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22Homozygous%20Deletion%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%7D&size=30&sort=start_position&format=tsv'
chromosome cnv_change cnv_change_5_category cnv_id end_position gene_level_cn id ncbi_build start_position
4 Loss Homozygous Deletion 8884174a-1a74-5fec-af2a-1abd816c4022 88208 True 8884174a-1a74-5fec-af2a-1abd816c4022 GRCh38 53286
4 Loss Homozygous Deletion 1dc3143b-99d8-5d9b-80a4-84a4e8967b37 202303 True 1dc3143b-99d8-5d9b-80a4-84a4e8967b37 GRCh38 124501
4 Loss Homozygous Deletion 1d656e18-64c3-51c1-856f-eba2a2bb4214 305474 True 1d656e18-64c3-51c1-856f-eba2a2bb4214 GRCh38 270675
4 Loss Homozygous Deletion a392d072-2650-5c7f-b3a6-d325680d87fb 384868 True a392d072-2650-5c7f-b3a6-d325680d87fb GRCh38 337814
4 Loss Homozygous Deletion 653d70d7-07fa-5b5a-8961-ba031060e33a 499156 True 653d70d7-07fa-5b5a-8961-ba031060e33a GRCh38 425815
4 Loss Homozygous Deletion a793c3d6-805b-531e-86fc-0b92eb3b8d98 540200 True a793c3d6-805b-531e-86fc-0b92eb3b8d98 GRCh38 499210
4 Loss Homozygous Deletion 6a7256cb-f674-58e1-8359-13045f0e5abc 576295 True 6a7256cb-f674-58e1-8359-13045f0e5abc GRCh38 573880
4 Loss Homozygous Deletion a055b2b3-8135-509c-b870-ef7ab693d394 670782 True a055b2b3-8135-509c-b870-ef7ab693d394 GRCh38 625573
4 Loss Homozygous Deletion b98c4b26-6c62-5a89-931a-bba7f882083e 674330 True b98c4b26-6c62-5a89-931a-bba7f882083e GRCh38 672436
4 Loss Homozygous Deletion efb72922-c8ee-51bd-9340-b6c24cf0e120 682033 True efb72922-c8ee-51bd-9340-b6c24cf0e120 GRCh38 673580
4 Loss Homozygous Deletion f7e8f2a0-50ba-57b7-9604-109de3832a0d 689271 True f7e8f2a0-50ba-57b7-9604-109de3832a0d GRCh38 681829
4 Loss Homozygous Deletion 8f439ea0-b792-5d31-a457-f01ead7351d4 770640 True 8f439ea0-b792-5d31-a457-f01ead7351d4 GRCh38 705748
4 Loss Homozygous Deletion c73f54a7-6c75-51c8-b9ee-9a0f9e649eca 826129 True c73f54a7-6c75-51c8-b9ee-9a0f9e649eca GRCh38 784957
4 Loss Homozygous Deletion f7fa174c-2c9b-5462-b807-a1f6d18b1320 932373 True f7fa174c-2c9b-5462-b807-a1f6d18b1320 GRCh38 849276
4 Loss Homozygous Deletion 3b7a64d1-f4d2-5186-ba74-07483d5f53c1 958656 True 3b7a64d1-f4d2-5186-ba74-07483d5f53c1 GRCh38 932387
4 Loss Homozygous Deletion a7457adc-31d0-5b5e-9fb2-53ff26f354ce 986895 True a7457adc-31d0-5b5e-9fb2-53ff26f354ce GRCh38 958887
4 Loss Homozygous Deletion 30d664ec-c0b6-5283-9342-5af09a882a05 993440 True 30d664ec-c0b6-5283-9342-5af09a882a05 GRCh38 979073
4 Loss Homozygous Deletion 88373fd0-771d-5ee2-870c-8b38b469b386 1004564 True 88373fd0-771d-5ee2-870c-8b38b469b386 GRCh38 986997
4 Loss Homozygous Deletion 282251fd-8556-5b32-b285-c63b58662263 1026898 True 282251fd-8556-5b32-b285-c63b58662263 GRCh38 1009936
4 Loss Homozygous Deletion 71480086-ef38-5ddb-a10b-e5165d207846 1113564 True 71480086-ef38-5ddb-a10b-e5165d207846 GRCh38 1056250
4 Loss Homozygous Deletion 2a87f0ba-7cda-51e6-914d-acc6ab42e4ce 1208962 True 2a87f0ba-7cda-51e6-914d-acc6ab42e4ce GRCh38 1166932
4 Loss Homozygous Deletion 99897d07-d376-559b-8bf5-5361467a3b11 1249953 True 99897d07-d376-559b-8bf5-5361467a3b11 GRCh38 1211445
4 Loss Homozygous Deletion 71980ad9-0561-5b17-8fa8-1c0280940a98 1340147 True 71980ad9-0561-5b17-8fa8-1c0280940a98 GRCh38 1289887
4 Loss Homozygous Deletion dc6f0cde-beb2-5b67-b279-66d993e4072b 1395989 True dc6f0cde-beb2-5b67-b279-66d993e4072b GRCh38 1345691
4 Loss Homozygous Deletion 3897b742-1fb0-59af-94a3-468f414954bb 1406442 True 3897b742-1fb0-59af-94a3-468f414954bb GRCh38 1402932
4 Loss Homozygous Deletion 35cdeb0b-9fb6-5d5c-9474-e94dc3d95dce 1684261 True 35cdeb0b-9fb6-5d5c-9474-e94dc3d95dce GRCh38 1617915
4 Loss Homozygous Deletion 3237ca12-ab72-5278-a57e-21ebfee6a408 1712344 True 3237ca12-ab72-5278-a57e-21ebfee6a408 GRCh38 1692731
4 Loss Homozygous Deletion 60664ffe-8c48-5f2b-bc6f-71408c876794 1745171 True 60664ffe-8c48-5f2b-bc6f-71408c876794 GRCh38 1712891
4 Loss Homozygous Deletion 967a8cd6-6b29-5a93-ab4d-7aa7cf696716 1721358 True 967a8cd6-6b29-5a93-ab4d-7aa7cf696716 GRCh38 1715952
4 Loss Homozygous Deletion 6846f70b-8327-555a-8486-f7036906465e 1808872 True 6846f70b-8327-555a-8486-f7036906465e GRCh38 1793293
Example 3: A user wants to determine the location and identity of the gene affected by the cnv 544c4896-0152-5787-8d77-894a16f0ded0, and determine whether the gene is found within the Cancer Gene Census.
curl 'https://api.gdc.cancer.gov/cnvs/544c4896-0152-5787-8d77-894a16f0ded0?pretty=true&expand=consequence.gene'
{
"data": {
"start_position": 27100354,
"consequence": [
{
"gene": {
"biotype": "protein_coding",
"symbol": "HOXA2",
"gene_id": "ENSG00000105996"
}
}
],
"gene_level_cn": true,
"cnv_change": "Gain",
"ncbi_build": "GRCh38",
"chromosome": "7",
"cnv_id": "544c4896-0152-5787-8d77-894a16f0ded0",
"end_position": 27102686
},
"warnings": {}
}
Copy Number Variation Occurrence Endpoint Examples
Example 1: A user is interested in finding cases that have both cnv and ssm data for females diagnosed with Squamous Cell Neoplasms and have a cnv gain change on chromosome 9. It is important to note that for a case like this, where multiple arguments are need for one filtered field, it is easier for the API to have multiple filters for the same field, case.available_variation_data in this example, than having one filter with multiple arguments.
{
"op": "and",
"content": [
{
"op": "in",
"content": {
"field": "cnv.cnv_change",
"value": [
"Gain"
]
}
},
{
"op": "in",
"content": {
"field": "case.demographic.gender",
"value": [
"female"
]
}
},
{
"op": "in",
"content": {
"field": "case.available_variation_data",
"value": [
"cnv"
]
}
},
{
"op": "in",
"content": {
"field": "case.available_variation_data",
"value": [
"ssm"
]
}
},
{
"op": "in",
"content": {
"field": "cnv.chromosome",
"value": [
"9"
]
}
},
{
"op": "in",
"content": {
"field": "case.disease_type",
"value": [
"Squamous Cell Neoplasms"
]
}
}
]
}
curl 'https://api.gdc.cancer.gov/cnv_occurrences?filters=%7B%0D%0A++++%22op%22%3A+%22and%22%2C%0D%0A++++%22content%22%3A+%5B%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv.cnv_change%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Gain%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.demographic.gender%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22female%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.available_variation_data%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22cnv%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.available_variation_data%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22ssm%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv.chromosome%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%229%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.disease_type%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Squamous+Cell+Neoplasms%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%0D%0A++++%5D%0D%0A%7D&fields=case.available_variation_data,case.case_id&format=tsv'
case.available_variation_data.0 case.available_variation_data.1 case.case_id id
cnv ssm da30a845-c4d3-4c78-b8b0-210239224f8f 3caf6e3b-024f-57b6-bdd9-3b67e423cc11
cnv ssm 0809ba8b-4ab6-4f43-934c-c1ccbc014a7e e6afe58e-c99c-5c8d-920e-8ba4daad4d89
cnv ssm 8e0e456e-85ee-4de5-8f0b-72393d6acde0 9d983d9c-8320-53f1-9054-e46926c5b834
cnv ssm 64a195f6-2212-4e81-bccc-e39c77a10908 8caeaecc-ad68-539d-8b3c-8320b3684763
cnv ssm 2f6a0e87-1e6c-41f3-93e0-3e505fa654b0 4862c166-0f37-5e3c-ae4e-a2964de01cea
cnv ssm f0daf315-8909-4cda-886d-a2770b08db94 099ff6cd-bd28-56f4-a181-6b02f3ba7503
cnv ssm ff3808e4-eece-4046-819b-fe1019317f8e 0c936aa2-393e-5463-a431-3613b4510021
cnv ssm 9205dc07-93f5-4b5e-924e-8e097616160f 133d27a7-fdc6-5082-a1f3-022b89f4e851
cnv ssm 79ae5209-f476-4d65-a6c0-ebc18d7c8942 7a5e6bb1-8af3-5964-a3cc-c53602c8b099
cnv ssm ff7099e1-8ff9-48e4-842d-46e98076e7e6 fb27fa8f-aa31-5e20-84da-8f45bb675405
Example 2: A user is interested in the first cnv occurrence (3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e) from the previous example, and would like to know more about the case exposures and demographics.
curl 'https://api.gdc.cancer.gov/cnv_occurrences/3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e?pretty=true&expand=cnv,case,case.exposures,case.demographic'
{
"data": {
"cnv": {
"start_position": 68815994,
"gene_level_cn": true,
"cnv_change": "Gain",
"ncbi_build": "GRCh38",
"chromosome": "4",
"variant_status": "Tumor Only",
"cnv_id": "1a889109-30d5-51e3-848f-9f615c69f407",
"end_position": 68832023
},
"cnv_occurrence_id": "3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e",
"case": {
"exposures": [
{
"cigarettes_per_day": 5.47945205479452,
"alcohol_history": "Not Reported",
"exposure_id": "f7b08a8e-d22b-5cb0-be9f-b922c9ca87d2",
"submitter_id": "TCGA-38-4629_exposure",
"state": "released",
"pack_years_smoked": 100.0
}
],
"primary_site": "Bronchus and lung",
"disease_type": "Adenomas and Adenocarcinomas",
"available_variation_data": [
"cnv",
"ssm"
],
"case_id": "127bf818-f7e5-46b5-a9de-39f6d96b8b83",
"submitter_id": "TCGA-38-4629",
"state": "released",
"demographic": {
"demographic_id": "9ea1f795-9510-5acc-a9a5-bf1379e6635a",
"ethnicity": "not hispanic or latino",
"gender": "male",
"race": "white",
"vital_status": "Dead",
"age_at_index": 68,
"submitter_id": "TCGA-38-4629_demographic",
"days_to_death": 864,
"days_to_birth": -25104,
"state": "released",
"year_of_death": 2005,
"year_of_birth": 1935
}
}
},
"warnings": {}
}
Example 3: A user is interested in finding cases that have cnv data for males diagnosed with gliomas and have a cnv amplification on chromosome 7.
{
"op": "and",
"content": [
{
"op": "in",
"content": {
"field": "cnv.cnv_change_5_category",
"value": [
"Amplification"
]
}
},
{
"op": "in",
"content": {
"field": "case.demographic.gender",
"value": [
"male"
]
}
},
{
"op": "in",
"content": {
"field": "case.available_variation_data",
"value": [
"cnv"
]
}
},
{
"op": "in",
"content": {
"field": "cnv.chromosome",
"value": [
"7"
]
}
},
{
"op": "in",
"content": {
"field": "case.disease_type",
"value": [
"Gliomas"
]
}
}
]
}
curl 'https://api.gdc.cancer.gov/cnv_occurrences?filters=%7B%0A%20%20%20%20%20%20%20%20%22op%22%3A%20%22and%22%2C%0A%20%20%20%20%20%20%20%20%22content%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22cnv.cnv_change_5_category%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22Amplification%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22case.demographic.gender%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22male%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22case.available_variation_data%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22cnv%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22cnv.chromosome%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%227%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22op%22%3A%20%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22content%22%3A%20%7B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%20%22case.disease_type%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%20%5B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22Gliomas%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%7D&fields=case.available_variation_data,case.case_id&format=tsv'
case.available_variation_data.0 case.available_variation_data.1 case.case_id id
cnv ssm a1da2f64-5a24-4e6b-abc1-e70aae23082c 15bbf08b-6d6a-5c1d-bd94-1e86710ce29a
cnv ssm 2e3b9f32-304e-454b-ac2c-fc72d2ccaa19 c9ff4332-959e-5e68-a305-29ae7f898a67
cnv 0133e584-111e-450a-b451-77a2799ef529 7d6ca206-7c41-5f3e-89d5-69106d3262cb
cnv ssm 50603cc6-42e6-412f-ab07-4805f728e6b6 eccbd36c-93a3-5644-aa30-6b06d66ac35b
cnv 372a4cc6-8fc9-4157-9cdc-fe020b176249 ea64dfc0-d297-5686-bcfc-3336201e7c01
cnv ssm 92f323c8-dae4-4fdc-a108-148ddc238d1a 4b07a619-ad6f-5169-af7f-3360cc2a8845
cnv ssm e349d8aa-bb82-4ce8-b14c-61216289f25b 4ae6c613-92be-5424-a5d6-305deb5b3cac
cnv ssm 6c5154d2-af36-492f-b520-d925528824e4 dcf8e315-e868-5dc2-8ca0-5f76d4f7e5ee
cnv ssm fbb0dc0d-6314-40ea-bc43-0cbf3b710dbe 504fd9f6-dc90-55c4-abf0-68ab38e17f61
cnv ssm 7cada85b-00b1-41e5-9924-e09eb077ad56 1e6f552a-78ed-5ce7-bef9-a55670c979db
scRNA-Seq Gene Expression Endpoints
This endpoint retrieves gene expression data for a specified case or file, returning normalized gene expression values across cell IDs. It requires specifying either a case_id or file_id, but not both, and a list of gene IDs. The file_id must correspond to a file in HDF5 format and up to 10 gene IDs can be queried per request. The gene expression values come from the main matrix '/matrix' layer of the HDF5 file.
Example 1: A user wants to retrieve scRNA-Seq gene expression data for a specific case. They want to query the expression levels of the gene identified by ENSG00000139618 across different cell IDs.
{
"case_id": "00a29522-5eb0-4dbe-ae63-875aba3bf1b1",
"gene_ids": [
"ENSG00000139618"
]
}
curl --location 'https://api.gdc.cancer.gov/scrna_seq/gene_expression' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--data '{
"case_id": "00a29522-5eb0-4dbe-ae63-875aba3bf1b1",
"gene_ids": [
"ENSG00000139618"
]
}'
{
"data": [
{
"case_id": "00a29522-5eb0-4dbe-ae63-875aba3bf1b1",
"file_id": "2a095c71-d5ba-4a8a-bacc-2391b52d8328",
"gene_id": "ENSG00000139618",
"cells": [
{
"cell_id": "AAACCCAAGCAATTAG-1",
"value": 0.0
},
{
"cell_id": "AAACCCAAGCCATTCA-1",
"value": 0.0
},
{
"cell_id": "AAACCCAAGTGGAAAG-1",
"value": 1.3862943611198906
},
{
"cell_id": "AAACCCACAACGGTAG-1",
"value": 0.0
},
{
"cell_id": "AAACCCACATCGCTCT-1",
"value": 0.0
},
{
"cell_id": "AAACCCAGTTAGAAAC-1",
"value": 0.0
},
{
"cell_id": "AAACCCATCAAGCTGT-1",
"value": 0.0
},
{
"cell_id": "AAACCCATCGACACTA-1",
"value": 0.0
},
{
"cell_id": "AAACCCATCTCCCATG-1",
"value": 0.0
},
{
"cell_id": "AAACGAAAGACTCTAC-1",
"value": 0.0
},
{
"cell_id": "AAACGAACACGGTCTG-1",
"value": 0.6931471805599453
},
{
"cell_id": "AAACGAAGTATCCTTT-1",
"value": 0.0
}
],
"errors": []
}
]
}
Example 2: A researcher wants to analyze the gene expression data associated with a specific file from a sequencing experiment. To perform this analysis, they query the expression levels of the genes identified by ENSG00000139618, ENSG00000141510, and ENSG00000181143 across different cell IDs using the file ID c8ea9c15-368d-460c-9775-5037a5f1790a.
{
"file_id": "c8ea9c15-368d-460c-9775-5037a5f1790a",
"gene_ids": [
"ENSG00000139618",
"ENSG00000141510",
"ENSG00000181143"
]
}
curl --location 'https://api.gdc.cancer.gov/scrna_seq/gene_expression' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--data '{
"file_id": "c8ea9c15-368d-460c-9775-5037a5f1790a",
"gene_ids": [
"ENSG00000139618",
"ENSG00000141510",
"ENSG00000181143"
]
}'
{
"data": [
{
"case_id": "aa7502a9-5ffe-48c1-a1a8-3b07e83f78d7",
"file_id": "c8ea9c15-368d-460c-9775-5037a5f1790a",
"gene_id": "ENSG00000139618",
"cells": [
{
"cell_id": "AAACCCACAAGGTCAG-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGACGAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGGGTAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACAGCGGTCT-1",
"value": 0.0
},
{
"cell_id": "AAACCCATCGCGTGCA-1",
"value": 0.0
},
{
"cell_id": "AAACGAACAAATCAGA-1",
"value": 1.0986122886681096
},
{
"cell_id": "AAACGAACACTTGTGA-1",
"value": 0.0
},
{
"cell_id": "TTTGTTGTCGCTCTCA-1",
"value": 0.0
}
],
"errors": []
},
{
"case_id": "aa7502a9-5ffe-48c1-a1a8-3b07e83f78d7",
"file_id": "c8ea9c15-368d-460c-9775-5037a5f1790a",
"gene_id": "ENSG00000141510",
"cells": [
{
"cell_id": "AAACCCACAAGGTCAG-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGACGAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGGGTAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACAGCGGTCT-1",
"value": 0.6931471805599453
},
{
"cell_id": "AAACCCATCGCGTGCA-1",
"value": 0.0
}
],
"errors": []
},
{
"case_id": "aa7502a9-5ffe-48c1-a1a8-3b07e83f78d7",
"file_id": "c8ea9c15-368d-460c-9775-5037a5f1790a",
"gene_id": "ENSG00000181143",
"cells": [
{
"cell_id": "AAACCCACAAGGTCAG-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGACGAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACACGGGTAA-1",
"value": 0.0
},
{
"cell_id": "AAACCCACAGCGGTCT-1",
"value": 0.0
},
{
"cell_id": "TTTGTTGTCGCTCTCA-1",
"value": 0.0
}
],
"errors": []
}
]
}
Analysis Endpoints
In addition to the ssms, ssm_occurrences, and genes endpoints mentioned previously, several /analysis endpoints were designed to quickly retrieve specific datasets used for visualization display.
Example 1: The /analysis/top_cases_counts_by_genes endpoint gives the number of cases with a mutation in each gene listed in the gene_ids parameter for each project. Note that this endpoint cannot be used with the format or fields parameters. In this instance, the query will produce the number of cases in each projects with mutations in the gene ENSG00000155657.
curl "https://api.gdc.cancer.gov/analysis/top_cases_counts_by_genes?gene_ids=ENSG00000155657&pretty=true"
This JSON-formatted output is broken up by project. For an example, see the following text:
$ curl "https://api.gdc.cancer.gov/analysis/top_cases_counts_by_genes?gene_ids=ENSG00000155657&pretty=true"
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 12,
"successful": 12,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 5967,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"projects": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "TCGA-BRCA",
"doc_count": 425,
"genes": {
"doc_count": 4031450,
"my_genes": {
"doc_count": 425,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 425
}
]
}
}
}
},
{
"key": "TCGA-LUSC",
"doc_count": 423,
"genes": {
"doc_count": 4123089,
"my_genes": {
"doc_count": 423,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 423
}
]
}
}
}
},
{
"key": "CPTAC-3",
"doc_count": 421,
"genes": {
"doc_count": 251552,
"my_genes": {
"doc_count": 421,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 421
}
]
}
}
}
},
{
"key": "TCGA-SKCM",
"doc_count": 391,
"genes": {
"doc_count": 3040929,
"my_genes": {
"doc_count": 391,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 391
}
]
}
}
}
},
{
"key": "TCGA-LUAD",
"doc_count": 345,
"genes": {
"doc_count": 3188761,
"my_genes": {
"doc_count": 345,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 345
}
]
}
}
}
},
{
"key": "TCGA-OV",
"doc_count": 341,
"genes": {
"doc_count": 3728561,
"my_genes": {
"doc_count": 341,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 341
}
]
}
}
}
},
{
"key": "TCGA-STAD",
"doc_count": 300,
"genes": {
"doc_count": 2145783,
"my_genes": {
"doc_count": 300,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 300
}
]
}
}
}
},
{
"key": "TCGA-UCEC",
"doc_count": 297,
"genes": {
"doc_count": 1637055,
"my_genes": {
"doc_count": 297,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 297
}
]
}
}
}
},
{
"key": "TCGA-HNSC",
"doc_count": 293,
"genes": {
"doc_count": 2325617,
"my_genes": {
"doc_count": 293,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 293
}
]
}
}
}
},
{
"key": "TCGA-COAD",
"doc_count": 288,
"genes": {
"doc_count": 1695280,
"my_genes": {
"doc_count": 288,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 288
}
]
}
}
}
},
{
"key": "TCGA-BLCA",
"doc_count": 280,
"genes": {
"doc_count": 2466835,
"my_genes": {
"doc_count": 280,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 280
}
]
}
}
}
},
{
"key": "MMRF-COMMPASS",
"doc_count": 181,
"genes": {
"doc_count": 45977,
"my_genes": {
"doc_count": 181,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 181
}
]
}
}
}
},
{
"key": "TCGA-LIHC",
"doc_count": 167,
"genes": {
"doc_count": 1216775,
"my_genes": {
"doc_count": 167,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 167
}
]
}
}
}
},
{
"key": "TCGA-CESC",
"doc_count": 161,
"genes": {
"doc_count": 1103281,
"my_genes": {
"doc_count": 161,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 161
}
]
}
}
}
},
{
"key": "TCGA-KIRC",
"doc_count": 161,
"genes": {
"doc_count": 842546,
"my_genes": {
"doc_count": 161,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 161
}
]
}
}
}
},
{
"key": "CPTAC-2",
"doc_count": 131,
"genes": {
"doc_count": 72575,
"my_genes": {
"doc_count": 131,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 131
}
]
}
}
}
},
{
"key": "TCGA-GBM",
"doc_count": 131,
"genes": {
"doc_count": 756809,
"my_genes": {
"doc_count": 131,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 131
}
]
}
}
}
},
{
"key": "TCGA-ESCA",
"doc_count": 129,
"genes": {
"doc_count": 1210888,
"my_genes": {
"doc_count": 129,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 129
}
]
}
}
}
},
{
"key": "TCGA-PRAD",
"doc_count": 101,
"genes": {
"doc_count": 379949,
"my_genes": {
"doc_count": 101,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 101
}
]
}
}
}
},
{
"key": "HCMI-CMDC",
"doc_count": 99,
"genes": {
"doc_count": 54829,
"my_genes": {
"doc_count": 99,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 99
}
]
}
}
}
},
{
"key": "TCGA-READ",
"doc_count": 98,
"genes": {
"doc_count": 726313,
"my_genes": {
"doc_count": 98,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 98
}
]
}
}
}
},
{
"key": "TCGA-LGG",
"doc_count": 95,
"genes": {
"doc_count": 424689,
"my_genes": {
"doc_count": 95,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 95
}
]
}
}
}
},
{
"key": "TCGA-KIRP",
"doc_count": 93,
"genes": {
"doc_count": 521936,
"my_genes": {
"doc_count": 93,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 93
}
]
}
}
}
},
{
"key": "TCGA-SARC",
"doc_count": 93,
"genes": {
"doc_count": 903111,
"my_genes": {
"doc_count": 93,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 93
}
]
}
}
}
},
{
"key": "TCGA-TGCT",
"doc_count": 51,
"genes": {
"doc_count": 524456,
"my_genes": {
"doc_count": 51,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 51
}
]
}
}
}
},
{
"key": "TARGET-ALL-P2",
"doc_count": 50,
"genes": {
"doc_count": 1882,
"my_genes": {
"doc_count": 50,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 50
}
]
}
}
}
},
{
"key": "TCGA-KICH",
"doc_count": 43,
"genes": {
"doc_count": 353674,
"my_genes": {
"doc_count": 43,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 43
}
]
}
}
}
},
{
"key": "TCGA-PAAD",
"doc_count": 43,
"genes": {
"doc_count": 300427,
"my_genes": {
"doc_count": 43,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 43
}
]
}
}
}
},
{
"key": "CGCI-HTMCP-CC",
"doc_count": 37,
"genes": {
"doc_count": 3606,
"my_genes": {
"doc_count": 37,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 37
}
]
}
}
}
},
{
"key": "CDDP_EAGLE-1",
"doc_count": 32,
"genes": {
"doc_count": 16980,
"my_genes": {
"doc_count": 32,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 32
}
]
}
}
}
},
{
"key": "TCGA-ACC",
"doc_count": 29,
"genes": {
"doc_count": 283969,
"my_genes": {
"doc_count": 29,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 29
}
]
}
}
}
},
{
"key": "CMI-MBC",
"doc_count": 28,
"genes": {
"doc_count": 3581,
"my_genes": {
"doc_count": 28,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 28
}
]
}
}
}
},
{
"key": "TCGA-THCA",
"doc_count": 28,
"genes": {
"doc_count": 89120,
"my_genes": {
"doc_count": 28,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 28
}
]
}
}
}
},
{
"key": "TCGA-UCS",
"doc_count": 28,
"genes": {
"doc_count": 283673,
"my_genes": {
"doc_count": 28,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 28
}
]
}
}
}
},
{
"key": "TCGA-MESO",
"doc_count": 21,
"genes": {
"doc_count": 137002,
"my_genes": {
"doc_count": 21,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 21
}
]
}
}
}
},
{
"key": "TCGA-PCPG",
"doc_count": 19,
"genes": {
"doc_count": 99444,
"my_genes": {
"doc_count": 19,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 19
}
]
}
}
}
},
{
"key": "TARGET-NBL",
"doc_count": 15,
"genes": {
"doc_count": 829,
"my_genes": {
"doc_count": 15,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 15
}
]
}
}
}
},
{
"key": "TCGA-UVM",
"doc_count": 12,
"genes": {
"doc_count": 68201,
"my_genes": {
"doc_count": 12,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 12
}
]
}
}
}
},
{
"key": "EXCEPTIONAL_RESPONDERS-ER",
"doc_count": 11,
"genes": {
"doc_count": 10617,
"my_genes": {
"doc_count": 11,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 11
}
]
}
}
}
},
{
"key": "TCGA-THYM",
"doc_count": 11,
"genes": {
"doc_count": 59647,
"my_genes": {
"doc_count": 11,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 11
}
]
}
}
}
},
{
"key": "BEATAML1.0-COHORT",
"doc_count": 10,
"genes": {
"doc_count": 279,
"my_genes": {
"doc_count": 10,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 10
}
]
}
}
}
},
{
"key": "TARGET-OS",
"doc_count": 10,
"genes": {
"doc_count": 414,
"my_genes": {
"doc_count": 10,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 10
}
]
}
}
}
},
{
"key": "TCGA-LAML",
"doc_count": 10,
"genes": {
"doc_count": 10175,
"my_genes": {
"doc_count": 10,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 10
}
]
}
}
}
},
{
"key": "TCGA-DLBC",
"doc_count": 9,
"genes": {
"doc_count": 63497,
"my_genes": {
"doc_count": 9,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 9
}
]
}
}
}
},
{
"key": "TCGA-CHOL",
"doc_count": 8,
"genes": {
"doc_count": 52960,
"my_genes": {
"doc_count": 8,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 8
}
]
}
}
}
},
{
"key": "CMI-MPC",
"doc_count": 7,
"genes": {
"doc_count": 365,
"my_genes": {
"doc_count": 7,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 7
}
]
}
}
}
},
{
"key": "CMI-ASC",
"doc_count": 6,
"genes": {
"doc_count": 5745,
"my_genes": {
"doc_count": 6,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 6
}
]
}
}
}
},
{
"key": "TARGET-WT",
"doc_count": 3,
"genes": {
"doc_count": 51,
"my_genes": {
"doc_count": 3,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 3
}
]
}
}
}
},
{
"key": "TARGET-ALL-P3",
"doc_count": 2,
"genes": {
"doc_count": 66,
"my_genes": {
"doc_count": 2,
"gene_id": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "ENSG00000155657",
"doc_count": 2
}
]
}
}
}
}
]
}
}
This portion of the output shows TCGA-GBM including 45 cases that have ssms in the gene ENSG00000155657.
Example 2: The following demonstrates a use of the /analysis/top_mutated_genes_by_project endpoint. This will output the genes that are mutated in the most cases in "TCGA-DLBC" and will count the mutations that have a HIGH or MODERATE impact on gene function. Note that the score field does not represent the number of mutations in a given gene, but a calculation that is used to determine which genes have the greatest number of unique mutations.
{
"op":"AND",
"content":[
{
"op":"in",
"content":{
"field":"case.project.project_id",
"value":[
"TCGA-DLBC"
]
}
},
{
"op":"in",
"content":{
"field":"case.ssm.consequence.transcript.annotation.vep_impact",
"value":[
"HIGH",
"MODERATE"
]
}
}
]
}
curl "https://api.gdc.cancer.gov/analysis/top_mutated_genes_by_project?fields=gene_id,symbol&filters=%7B%20%20%0A%20%20%20%22op%22%3A%22AND%20%20%20%22content%22%3A%5B%20%20%0A%20%20%20%20%20%20%7B%20%20%0A%20%20%20%20%20%20%20%20%20%22op%22%3A%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%22content%22%3A%7B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%22case.project.project_id%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%5B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22TCGA-DLBC%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%7B%20%20%0A%20%20%20%20%20%20%20%20%20%22op%22%3A%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%22content%22%3A%7B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%22case.ssm.consequence.transcript.annotation.vep_impact%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%5B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22HIGH%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22MODERATE%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%7D%0A%20%20%20%5D%0A%7D%0A&pretty=true"
{
"data": {
"hits": [
{
"symbol": "KMT2D",
"gene_id": "ENSG00000167548",
"_score": 13.0
},
{
"symbol": "BTG2",
"gene_id": "ENSG00000159388",
"_score": 13.0
},
{
"symbol": "B2M",
"gene_id": "ENSG00000166710",
"_score": 11.0
},
{
"symbol": "PIM1",
"gene_id": "ENSG00000137193",
"_score": 10.0
},
{
"symbol": "IGHG1",
"gene_id": "ENSG00000211896",
"_score": 10.0
},
{
"symbol": "CARD11",
"gene_id": "ENSG00000198286",
"_score": 10.0
},
{
"symbol": "H1-4",
"gene_id": "ENSG00000168298",
"_score": 9.0
},
{
"symbol": "PCLO",
"gene_id": "ENSG00000186472",
"_score": 9.0
},
{
"symbol": "IGHG2",
"gene_id": "ENSG00000211893",
"_score": 9.0
},
{
"symbol": "FAT4",
"gene_id": "ENSG00000196159",
"_score": 8.0
}
],
"pagination": {
"count": 10,
"total": 3500,
"size": 10,
"from": 0,
"sort": "None",
"page": 1,
"pages": 350
}
},
"warnings": {}
}
Example 3: The /analysis/top_mutated_cases_by_gene endpoint will generate information about the cases that are most affected by mutations in a given number of genes. Below, the file count for each category is given for the cases most affected by mutations in these 50 genes. The size of the output is limited to two cases with the size=2 parameter, but a higher value can be set by the user.
curl "https://api.gdc.cancer.gov/analysis/top_mutated_cases_by_gene?fields=diagnoses.age_at_diagnosis,diagnoses.primary_diagnosis,demographic.gender,demographic.race,demographic.ethnicity,case_id,summary.data_categories.file_count,summary.data_categories.data_category&filters=%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-DLBC%22%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22genes.gene_id%22%2C%22value%22%3A%5B%22ENSG00000166710%22%2C%22ENSG00000005339%22%2C%22ENSG00000083857%22%2C%22ENSG00000168769%22%2C%22ENSG00000100906%22%2C%22ENSG00000184677%22%2C%22ENSG00000101680%22%2C%22ENSG00000101266%22%2C%22ENSG00000028277%22%2C%22ENSG00000140968%22%2C%22ENSG00000181827%22%2C%22ENSG00000116815%22%2C%22ENSG00000275221%22%2C%22ENSG00000139083%22%2C%22ENSG00000112851%22%2C%22ENSG00000112697%22%2C%22ENSG00000164134%22%2C%22ENSG00000009413%22%2C%22ENSG00000071626%22%2C%22ENSG00000135407%22%2C%22ENSG00000101825%22%2C%22ENSG00000104814%22%2C%22ENSG00000166415%22%2C%22ENSG00000142867%22%2C%22ENSG00000254585%22%2C%22ENSG00000139718%22%2C%22ENSG00000077721%22%2C%22ENSG00000130294%22%2C%22ENSG00000117245%22%2C%22ENSG00000117318%22%2C%22ENSG00000270550%22%2C%22ENSG00000163637%22%2C%22ENSG00000166575%22%2C%22ENSG00000065526%22%2C%22ENSG00000156453%22%2C%22ENSG00000128191%22%2C%22ENSG00000055609%22%2C%22ENSG00000204469%22%2C%22ENSG00000187605%22%2C%22ENSG00000185875%22%2C%22ENSG00000110888%22%2C%22ENSG00000007341%22%2C%22ENSG00000173198%22%2C%22ENSG00000115568%22%2C%22ENSG00000163714%22%2C%22ENSG00000125772%22%2C%22ENSG00000080815%22%2C%22ENSG00000189079%22%2C%22ENSG00000120837%22%2C%22ENSG00000143951%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22ssms.consequence.transcript.annotation.vep_impact%22%2C%22value%22%3A%5B%22HIGH%22%5D%7D%7D%5D%7D&pretty=true&size=2"
{
"data": {
"hits": [
{
"summary": {
"data_categories": [
{
"file_count": 6,
"data_category": "Sequencing Reads"
},
{
"file_count": 14,
"data_category": "Biospecimen"
},
{
"file_count": 8,
"data_category": "Copy Number Variation"
},
{
"file_count": 16,
"data_category": "Simple Nucleotide Variation"
},
{
"file_count": 4,
"data_category": "Transcriptome Profiling"
},
{
"file_count": 3,
"data_category": "DNA Methylation"
},
{
"file_count": 8,
"data_category": "Clinical"
},
{
"file_count": 4,
"data_category": "Structural Variation"
},
{
"file_count": 1,
"data_category": "Proteome Profiling"
}
]
},
"case_id": "eda9496e-be80-4a13-bf06-89f0cc9e937f",
"diagnoses": [
{
"age_at_diagnosis": 18691,
"primary_diagnosis": "Malignant lymphoma, large B-cell, diffuse, NOS"
}
],
"demographic": {
"ethnicity": "hispanic or latino",
"gender": "male",
"race": "white"
},
"_score": 7.0
},
{
"summary": {
"data_categories": [
{
"file_count": 4,
"data_category": "Sequencing Reads"
},
{
"file_count": 13,
"data_category": "Biospecimen"
},
{
"file_count": 8,
"data_category": "Copy Number Variation"
},
{
"file_count": 16,
"data_category": "Simple Nucleotide Variation"
},
{
"file_count": 2,
"data_category": "Transcriptome Profiling"
},
{
"file_count": 3,
"data_category": "DNA Methylation"
},
{
"file_count": 8,
"data_category": "Clinical"
},
{
"file_count": 4,
"data_category": "Structural Variation"
}
]
},
"case_id": "7a589441-11ef-4158-87e7-3951d86bc2aa",
"diagnoses": [
{
"age_at_diagnosis": 20812,
"primary_diagnosis": "Malignant lymphoma, large B-cell, diffuse, NOS"
}
],
"demographic": {
"ethnicity": "not hispanic or latino",
"gender": "female",
"race": "white"
},
"_score": 4.0
}
],
"pagination": {
"count": 2,
"total": 32,
"size": 2,
"from": 0,
"sort": "None",
"page": 1,
"pages": 16
}
},
"warnings": {}
}
Example 4: The /analysis/mutated_cases_count_by_project endpoint produces counts for the number of cases that have associated ssm data in each project. The number of affected cases can be found under "case_with_ssm": {"doc_count": $case_count}.
curl "https://api.gdc.cancer.gov/analysis/mutated_cases_count_by_project?size=0&pretty=true"
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 12,
"successful": 12,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 44451,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"projects": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "FM-AD",
"doc_count": 18004,
"case_summary": {
"doc_count": 54012,
"case_with_ssm": {
"doc_count": 18004
}
}
},
{
"key": "TARGET-AML",
"doc_count": 2492,
"case_summary": {
"doc_count": 10780,
"case_with_ssm": {
"doc_count": 22
}
}
},
{
"key": "TARGET-ALL-P2",
"doc_count": 1587,
"case_summary": {
"doc_count": 5562,
"case_with_ssm": {
"doc_count": 717
}
}
},
{
"key": "MP2PRT-ALL",
"doc_count": 1510,
"case_summary": {
"doc_count": 10472,
"case_with_ssm": {
"doc_count": 1508
}
}
},
{
"key": "CPTAC-3",
"doc_count": 1235,
"case_summary": {
"doc_count": 8508,
"case_with_ssm": {
"doc_count": 1218
}
}
},
{
"key": "TARGET-NBL",
"doc_count": 1132,
"case_summary": {
"doc_count": 3007,
"case_with_ssm": {
"doc_count": 220
}
}
},
{
"key": "TCGA-BRCA",
"doc_count": 1098,
"case_summary": {
"doc_count": 9735,
"case_with_ssm": {
"doc_count": 1098
}
}
},
{
"key": "MMRF-COMMPASS",
"doc_count": 995,
"case_summary": {
"doc_count": 3528,
"case_with_ssm": {
"doc_count": 959
}
}
},
{
"key": "BEATAML1.0-COHORT",
"doc_count": 826,
"case_summary": {
"doc_count": 2891,
"case_with_ssm": {
"doc_count": 759
}
}
},
{
"key": "TARGET-WT",
"doc_count": 652,
"case_summary": {
"doc_count": 3045,
"case_with_ssm": {
"doc_count": 631
}
}
},
{
"key": "TCGA-GBM",
"doc_count": 617,
"case_summary": {
"doc_count": 3867,
"case_with_ssm": {
"doc_count": 600
}
}
},
{
"key": "TCGA-OV",
"doc_count": 608,
"case_summary": {
"doc_count": 5028,
"case_with_ssm": {
"doc_count": 599
}
}
},
{
"key": "TCGA-LUAD",
"doc_count": 585,
"case_summary": {
"doc_count": 4825,
"case_with_ssm": {
"doc_count": 571
}
}
},
{
"key": "TCGA-UCEC",
"doc_count": 560,
"case_summary": {
"doc_count": 4559,
"case_with_ssm": {
"doc_count": 559
}
}
},
{
"key": "TCGA-KIRC",
"doc_count": 537,
"case_summary": {
"doc_count": 4768,
"case_with_ssm": {
"doc_count": 534
}
}
},
{
"key": "TCGA-HNSC",
"doc_count": 528,
"case_summary": {
"doc_count": 4577,
"case_with_ssm": {
"doc_count": 528
}
}
},
{
"key": "TCGA-LGG",
"doc_count": 516,
"case_summary": {
"doc_count": 4570,
"case_with_ssm": {
"doc_count": 516
}
}
},
{
"key": "TCGA-THCA",
"doc_count": 507,
"case_summary": {
"doc_count": 4442,
"case_with_ssm": {
"doc_count": 507
}
}
},
{
"key": "TCGA-LUSC",
"doc_count": 504,
"case_summary": {
"doc_count": 4425,
"case_with_ssm": {
"doc_count": 504
}
}
},
{
"key": "TCGA-PRAD",
"doc_count": 500,
"case_summary": {
"doc_count": 4365,
"case_with_ssm": {
"doc_count": 500
}
}
},
{
"key": "NCICCR-DLBCL",
"doc_count": 489,
"case_summary": {
"doc_count": 1451,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "TCGA-SKCM",
"doc_count": 470,
"case_summary": {
"doc_count": 4125,
"case_with_ssm": {
"doc_count": 470
}
}
},
{
"key": "TCGA-COAD",
"doc_count": 461,
"case_summary": {
"doc_count": 3888,
"case_with_ssm": {
"doc_count": 461
}
}
},
{
"key": "TCGA-STAD",
"doc_count": 443,
"case_summary": {
"doc_count": 3884,
"case_with_ssm": {
"doc_count": 443
}
}
},
{
"key": "REBC-THYR",
"doc_count": 440,
"case_summary": {
"doc_count": 2456,
"case_with_ssm": {
"doc_count": 380
}
}
},
{
"key": "TCGA-BLCA",
"doc_count": 412,
"case_summary": {
"doc_count": 3645,
"case_with_ssm": {
"doc_count": 412
}
}
},
{
"key": "TARGET-OS",
"doc_count": 383,
"case_summary": {
"doc_count": 1276,
"case_with_ssm": {
"doc_count": 97
}
}
},
{
"key": "TCGA-LIHC",
"doc_count": 377,
"case_summary": {
"doc_count": 3204,
"case_with_ssm": {
"doc_count": 377
}
}
},
{
"key": "CPTAC-2",
"doc_count": 342,
"case_summary": {
"doc_count": 1349,
"case_with_ssm": {
"doc_count": 328
}
}
},
{
"key": "TRIO-CRU",
"doc_count": 339,
"case_summary": {
"doc_count": 339,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "CGCI-BLGSP",
"doc_count": 324,
"case_summary": {
"doc_count": 2076,
"case_with_ssm": {
"doc_count": 262
}
}
},
{
"key": "TCGA-CESC",
"doc_count": 307,
"case_summary": {
"doc_count": 2623,
"case_with_ssm": {
"doc_count": 306
}
}
},
{
"key": "TCGA-KIRP",
"doc_count": 291,
"case_summary": {
"doc_count": 2568,
"case_with_ssm": {
"doc_count": 291
}
}
},
{
"key": "HCMI-CMDC",
"doc_count": 278,
"case_summary": {
"doc_count": 2420,
"case_with_ssm": {
"doc_count": 277
}
}
},
{
"key": "TCGA-TGCT",
"doc_count": 263,
"case_summary": {
"doc_count": 2124,
"case_with_ssm": {
"doc_count": 262
}
}
},
{
"key": "TCGA-SARC",
"doc_count": 261,
"case_summary": {
"doc_count": 2309,
"case_with_ssm": {
"doc_count": 261
}
}
},
{
"key": "CGCI-HTMCP-CC",
"doc_count": 212,
"case_summary": {
"doc_count": 1452,
"case_with_ssm": {
"doc_count": 206
}
}
},
{
"key": "CMI-MBC",
"doc_count": 200,
"case_summary": {
"doc_count": 653,
"case_with_ssm": {
"doc_count": 174
}
}
},
{
"key": "TCGA-LAML",
"doc_count": 200,
"case_summary": {
"doc_count": 1533,
"case_with_ssm": {
"doc_count": 200
}
}
},
{
"key": "TARGET-ALL-P3",
"doc_count": 191,
"case_summary": {
"doc_count": 782,
"case_with_ssm": {
"doc_count": 86
}
}
},
{
"key": "TCGA-ESCA",
"doc_count": 185,
"case_summary": {
"doc_count": 1623,
"case_with_ssm": {
"doc_count": 185
}
}
},
{
"key": "TCGA-PAAD",
"doc_count": 185,
"case_summary": {
"doc_count": 1720,
"case_with_ssm": {
"doc_count": 185
}
}
},
{
"key": "TCGA-PCPG",
"doc_count": 179,
"case_summary": {
"doc_count": 1512,
"case_with_ssm": {
"doc_count": 179
}
}
},
{
"key": "OHSU-CNL",
"doc_count": 176,
"case_summary": {
"doc_count": 494,
"case_with_ssm": {
"doc_count": 158
}
}
},
{
"key": "TCGA-READ",
"doc_count": 172,
"case_summary": {
"doc_count": 1414,
"case_with_ssm": {
"doc_count": 171
}
}
},
{
"key": "TCGA-THYM",
"doc_count": 124,
"case_summary": {
"doc_count": 1078,
"case_with_ssm": {
"doc_count": 124
}
}
},
{
"key": "TCGA-KICH",
"doc_count": 113,
"case_summary": {
"doc_count": 705,
"case_with_ssm": {
"doc_count": 66
}
}
},
{
"key": "WCDT-MCRPC",
"doc_count": 101,
"case_summary": {
"doc_count": 299,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "TCGA-ACC",
"doc_count": 92,
"case_summary": {
"doc_count": 809,
"case_with_ssm": {
"doc_count": 92
}
}
},
{
"key": "APOLLO-LUAD",
"doc_count": 87,
"case_summary": {
"doc_count": 510,
"case_with_ssm": {
"doc_count": 83
}
}
},
{
"key": "TCGA-MESO",
"doc_count": 87,
"case_summary": {
"doc_count": 813,
"case_with_ssm": {
"doc_count": 87
}
}
},
{
"key": "EXCEPTIONAL_RESPONDERS-ER",
"doc_count": 84,
"case_summary": {
"doc_count": 412,
"case_with_ssm": {
"doc_count": 20
}
}
},
{
"key": "TCGA-UVM",
"doc_count": 80,
"case_summary": {
"doc_count": 700,
"case_with_ssm": {
"doc_count": 80
}
}
},
{
"key": "CGCI-HTMCP-DLBCL",
"doc_count": 70,
"case_summary": {
"doc_count": 465,
"case_with_ssm": {
"doc_count": 50
}
}
},
{
"key": "ORGANOID-PANCREATIC",
"doc_count": 70,
"case_summary": {
"doc_count": 225,
"case_with_ssm": {
"doc_count": 57
}
}
},
{
"key": "TARGET-RT",
"doc_count": 69,
"case_summary": {
"doc_count": 404,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "CMI-MPC",
"doc_count": 63,
"case_summary": {
"doc_count": 199,
"case_with_ssm": {
"doc_count": 60
}
}
},
{
"key": "MATCH-I",
"doc_count": 60,
"case_summary": {
"doc_count": 345,
"case_with_ssm": {
"doc_count": 57
}
}
},
{
"key": "TCGA-DLBC",
"doc_count": 58,
"case_summary": {
"doc_count": 441,
"case_with_ssm": {
"doc_count": 50
}
}
},
{
"key": "TCGA-UCS",
"doc_count": 57,
"case_summary": {
"doc_count": 504,
"case_with_ssm": {
"doc_count": 57
}
}
},
{
"key": "BEATAML1.0-CRENOLANIB",
"doc_count": 56,
"case_summary": {
"doc_count": 107,
"case_with_ssm": {
"doc_count": 51
}
}
},
{
"key": "MP2PRT-WT",
"doc_count": 52,
"case_summary": {
"doc_count": 361,
"case_with_ssm": {
"doc_count": 51
}
}
},
{
"key": "TCGA-CHOL",
"doc_count": 51,
"case_summary": {
"doc_count": 378,
"case_with_ssm": {
"doc_count": 51
}
}
},
{
"key": "CDDP_EAGLE-1",
"doc_count": 50,
"case_summary": {
"doc_count": 384,
"case_with_ssm": {
"doc_count": 50
}
}
},
{
"key": "CTSP-DLBCL1",
"doc_count": 45,
"case_summary": {
"doc_count": 201,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "MATCH-W",
"doc_count": 45,
"case_summary": {
"doc_count": 265,
"case_with_ssm": {
"doc_count": 44
}
}
},
{
"key": "MATCH-Z1A",
"doc_count": 45,
"case_summary": {
"doc_count": 262,
"case_with_ssm": {
"doc_count": 43
}
}
},
{
"key": "CGCI-HTMCP-LC",
"doc_count": 39,
"case_summary": {
"doc_count": 292,
"case_with_ssm": {
"doc_count": 34
}
}
},
{
"key": "CMI-ASC",
"doc_count": 36,
"case_summary": {
"doc_count": 124,
"case_with_ssm": {
"doc_count": 36
}
}
},
{
"key": "MATCH-Z1D",
"doc_count": 36,
"case_summary": {
"doc_count": 212,
"case_with_ssm": {
"doc_count": 34
}
}
},
{
"key": "MATCH-Q",
"doc_count": 35,
"case_summary": {
"doc_count": 203,
"case_with_ssm": {
"doc_count": 34
}
}
},
{
"key": "MATCH-B",
"doc_count": 33,
"case_summary": {
"doc_count": 187,
"case_with_ssm": {
"doc_count": 32
}
}
},
{
"key": "MATCH-Y",
"doc_count": 31,
"case_summary": {
"doc_count": 181,
"case_with_ssm": {
"doc_count": 30
}
}
},
{
"key": "TARGET-ALL-P1",
"doc_count": 24,
"case_summary": {
"doc_count": 86,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "MATCH-U",
"doc_count": 23,
"case_summary": {
"doc_count": 137,
"case_with_ssm": {
"doc_count": 22
}
}
},
{
"key": "MATCH-H",
"doc_count": 21,
"case_summary": {
"doc_count": 122,
"case_with_ssm": {
"doc_count": 21
}
}
},
{
"key": "MATCH-N",
"doc_count": 21,
"case_summary": {
"doc_count": 120,
"case_with_ssm": {
"doc_count": 21
}
}
},
{
"key": "TARGET-CCSK",
"doc_count": 13,
"case_summary": {
"doc_count": 100,
"case_with_ssm": {
"doc_count": 0
}
}
},
{
"key": "VAREPOP-APOLLO",
"doc_count": 7,
"case_summary": {
"doc_count": 14,
"case_with_ssm": {
"doc_count": 7
}
}
}
]
}
}
}
Survival Analysis Endpoint
Survival plots are generated for different subsets of data, based on variants or projects, in the GDC Data Portal. The /analysis/survival endpoint can be used to programmatically retrieve the raw data used to generate these plots and apply different filters. Note that the fields and format parameters cannot be modified.
Example 1: A user wants to download data to generate a survival plot for cases from the project TCGA-DLBC.
curl "https://api.gdc.cancer.gov/analysis/survival?filters=%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-DLBC%22%7D%7D%5D&pretty=true"
{
"results": [
{
"meta": {
"id": 139834474037000
},
"donors": [
{
"time": 1.0,
"censored": true,
"survivalEstimate": 1,
"id": "dc87a809-95de-4eb7-a1c2-2650475f2d7e",
"submitter_id": "TCGA-RQ-A6JB",
"project_id": "TCGA-DLBC"
},
{
"time": 17.0,
"censored": true,
"survivalEstimate": 1,
"id": "4dd86ebd-ef16-4b2b-9ea0-5d1d7afef257",
"submitter_id": "TCGA-RQ-AAAT",
"project_id": "TCGA-DLBC"
},
{
"time": 58,
"censored": false,
"survivalEstimate": 1,
"id": "0bf573ac-cd1e-42d8-90cf-b30d7b08679c",
"submitter_id": "TCGA-FA-A6HN",
"project_id": "TCGA-DLBC"
},
{
"time": 126.0,
"censored": true,
"survivalEstimate": 0.9777777777777777,
"id": "f978cb0f-d319-4c01-b4c5-23ae1403a106",
"submitter_id": "TCGA-FF-8047",
"project_id": "TCGA-DLBC"
},
{
"time": 132.0,
"censored": true,
"survivalEstimate": 0.9777777777777777,
"id": "1843c82e-7a35-474f-9f79-c0a9af9aa09c",
"submitter_id": "TCGA-FA-A4BB",
"project_id": "TCGA-DLBC"
},
{
"time": 132.0,
"censored": true,
"survivalEstimate": 0.9777777777777777,
"id": "a43e5f0e-a21f-48d8-97e0-084d413680b7",
"submitter_id": "TCGA-FA-8693",
"project_id": "TCGA-DLBC"
},
{
"time": 248,
"censored": false,
"survivalEstimate": 0.9777777777777777,
"id": "0030a28c-81aa-44b0-8be0-b35e1dcbf98c",
"submitter_id": "TCGA-FA-A7Q1",
"project_id": "TCGA-DLBC"
},
{
"time": 298.0,
"censored": true,
"survivalEstimate": 0.9539295392953929,
"id": "f553f1a9-ecf2-4783-a609-6adca7c4c597",
"submitter_id": "TCGA-FF-A7CQ",
"project_id": "TCGA-DLBC"
},
{
"time": 313,
"censored": false,
"survivalEstimate": 0.9539295392953929,
"id": "f784bc3a-751b-4025-aab2-0af2f6f24266",
"submitter_id": "TCGA-FF-A7CR",
"project_id": "TCGA-DLBC"
},
{
"time": 385.0,
"censored": true,
"survivalEstimate": 0.929469807518588,
"id": "29e3d122-15a1-4235-a356-b1a9f94ceb39",
"submitter_id": "TCGA-FF-A7CX",
"project_id": "TCGA-DLBC"
},
{
"time": 391,
"censored": false,
"survivalEstimate": 0.929469807518588,
"id": "0e251c03-bf86-4ed8-b45d-3cbc97160502",
"submitter_id": "TCGA-GS-A9U4",
"project_id": "TCGA-DLBC"
},
{
"time": 427.0,
"censored": true,
"survivalEstimate": 0.9043490019099776,
"id": "e6365b38-bc44-400c-b4aa-18ce8ff5bfce",
"submitter_id": "TCGA-FA-A82F",
"project_id": "TCGA-DLBC"
},
{
"time": 553.0,
"censored": true,
"survivalEstimate": 0.9043490019099776,
"id": "b56bdbdb-43af-4a03-a072-54dd22d7550c",
"submitter_id": "TCGA-FA-A86F",
"project_id": "TCGA-DLBC"
},
{
"time": 595,
"censored": false,
"survivalEstimate": 0.9043490019099776,
"id": "31bbad4e-3789-42ec-9faa-1cb86970f723",
"submitter_id": "TCGA-G8-6907",
"project_id": "TCGA-DLBC"
},
{
"time": 679.0,
"censored": true,
"survivalEstimate": 0.8777505018538018,
"id": "0e9fcccc-0630-408d-a121-2c6413824cb7",
"submitter_id": "TCGA-FF-8062",
"project_id": "TCGA-DLBC"
},
{
"time": 708,
"censored": false,
"survivalEstimate": 0.8777505018538018,
"id": "a5b188f0-a6d3-4d4a-b04f-36d47ec05338",
"submitter_id": "TCGA-FA-A4XK",
"project_id": "TCGA-DLBC"
},
{
"time": 719.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "ed746cb9-0f2f-48ce-923a-3a9f9f00b331",
"submitter_id": "TCGA-FA-A7DS",
"project_id": "TCGA-DLBC"
},
{
"time": 730.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "c85f340e-584b-4f3b-b6a5-540491fc8ad2",
"submitter_id": "TCGA-GS-A9TV",
"project_id": "TCGA-DLBC"
},
{
"time": 749.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "69f23725-adca-48ac-9b33-80a7aae24cfe",
"submitter_id": "TCGA-FA-A6HO",
"project_id": "TCGA-DLBC"
},
{
"time": 751.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "67325322-483f-443f-9ffa-2a20d108a2fb",
"submitter_id": "TCGA-FF-8046",
"project_id": "TCGA-DLBC"
},
{
"time": 765.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "eda9496e-be80-4a13-bf06-89f0cc9e937f",
"submitter_id": "TCGA-GS-A9TZ",
"project_id": "TCGA-DLBC"
},
{
"time": 788.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "25ff86af-beb4-480c-b706-f3fe0306f7cf",
"submitter_id": "TCGA-RQ-A68N",
"project_id": "TCGA-DLBC"
},
{
"time": 791.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "1d0db5d7-39ca-466d-96b3-0d278c5ea768",
"submitter_id": "TCGA-FF-A7CW",
"project_id": "TCGA-DLBC"
},
{
"time": 832.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "c8cde9ea-89e9-4ee8-8a46-417a48f6d3ab",
"submitter_id": "TCGA-FF-8061",
"project_id": "TCGA-DLBC"
},
{
"time": 946.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "f0a326d2-1f3e-4a5d-bca8-32aaccc52338",
"submitter_id": "TCGA-FF-8042",
"project_id": "TCGA-DLBC"
},
{
"time": 965.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "a8e2df1e-4042-42af-9231-3a00e83489f0",
"submitter_id": "TCGA-FF-8043",
"project_id": "TCGA-DLBC"
},
{
"time": 972.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "e56e4d9c-052e-4ec6-a81b-dbd53e9c8ffe",
"submitter_id": "TCGA-FM-8000",
"project_id": "TCGA-DLBC"
},
{
"time": 982.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "45b0cf9f-a879-417f-8f39-7770552252c0",
"submitter_id": "TCGA-GS-A9TQ",
"project_id": "TCGA-DLBC"
},
{
"time": 1081.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "1f971af1-6772-4fe6-8d35-bbe527a037fe",
"submitter_id": "TCGA-FF-8041",
"project_id": "TCGA-DLBC"
},
{
"time": 1163.0,
"censored": true,
"survivalEstimate": 0.8503207986708705,
"id": "33365d22-cb83-4d8e-a2d1-06b675f75f6e",
"submitter_id": "TCGA-GS-A9TT",
"project_id": "TCGA-DLBC"
},
{
"time": 1252,
"censored": false,
"survivalEstimate": 0.8503207986708705,
"id": "6a21c948-cd85-4150-8c01-83017d7dc1ed",
"submitter_id": "TCGA-G8-6324",
"project_id": "TCGA-DLBC"
},
{
"time": 1299.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "f855dad1-6ffc-493e-ba6c-970874bc9210",
"submitter_id": "TCGA-GR-A4D5",
"project_id": "TCGA-DLBC"
},
{
"time": 1334.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "c1c06604-5ae2-4a53-b9c0-eb210d38e3f0",
"submitter_id": "TCGA-GR-A4D6",
"project_id": "TCGA-DLBC"
},
{
"time": 1373.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "58e66976-4507-4552-ac53-83a49a142dde",
"submitter_id": "TCGA-GS-A9TX",
"project_id": "TCGA-DLBC"
},
{
"time": 1581.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "ea54dbad-1b23-41cc-9378-d4002a8fca51",
"submitter_id": "TCGA-G8-6325",
"project_id": "TCGA-DLBC"
},
{
"time": 1581.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "d7df78b5-24f1-4ff4-bd9b-f0e6bec8289a",
"submitter_id": "TCGA-GR-A4D4",
"project_id": "TCGA-DLBC"
},
{
"time": 1617.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "29aff186-c321-4ff9-b81b-105e27e620ff",
"submitter_id": "TCGA-GS-A9TW",
"project_id": "TCGA-DLBC"
},
{
"time": 1739.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "5eff68ff-f6c3-40c9-9fc8-00e684a7b712",
"submitter_id": "TCGA-GR-A4D9",
"project_id": "TCGA-DLBC"
},
{
"time": 2131.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "f8cf647b-1447-4ac3-8c43-bef07765cabf",
"submitter_id": "TCGA-G8-6326",
"project_id": "TCGA-DLBC"
},
{
"time": 2616.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "6e9437f0-a4ed-475c-ab0e-bf1431c70a90",
"submitter_id": "TCGA-GS-A9TY",
"project_id": "TCGA-DLBC"
},
{
"time": 2983.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "c3d662ee-48d0-454a-bb0c-77d3338d3747",
"submitter_id": "TCGA-GR-7353",
"project_id": "TCGA-DLBC"
},
{
"time": 3394.0,
"censored": true,
"survivalEstimate": 0.8003019281608192,
"id": "fdecb74f-ac4e-46b1-b23a-5f7fde96ef9f",
"submitter_id": "TCGA-GS-A9U3",
"project_id": "TCGA-DLBC"
},
{
"time": 3553,
"censored": false,
"survivalEstimate": 0.8003019281608192,
"id": "a468e725-ad4b-411d-ac5c-2eacc68ec580",
"submitter_id": "TCGA-G8-6909",
"project_id": "TCGA-DLBC"
},
{
"time": 3897.0,
"censored": true,
"survivalEstimate": 0.6402415425286554,
"id": "1ea575f1-f731-408b-a629-f5f4abab569e",
"submitter_id": "TCGA-GS-A9TU",
"project_id": "TCGA-DLBC"
},
{
"time": 4578.0,
"censored": true,
"survivalEstimate": 0.6402415425286554,
"id": "7a589441-11ef-4158-87e7-3951d86bc2aa",
"submitter_id": "TCGA-GR-7351",
"project_id": "TCGA-DLBC"
},
{
"time": 5980.0,
"censored": true,
"survivalEstimate": 0.6402415425286554,
"id": "3622cf29-600f-4410-84d4-a9afeb41c475",
"submitter_id": "TCGA-G8-6914",
"project_id": "TCGA-DLBC"
},
{
"time": 6425,
"censored": false,
"survivalEstimate": 0.6402415425286554,
"id": "3f5a897d-1eaa-4d4c-8324-27ac07c90927",
"submitter_id": "TCGA-G8-6906",
"project_id": "TCGA-DLBC"
}
]
}
],
"overallStats": {}
}
Example 2: Here the survival endpoint is used to compare two survival plots for TCGA-BRCA cases. One plot will display survival information about cases with a particular mutation (in this instance: chr3:g.179234297A>G) and the other plot will display information about cases without that mutation. This type of query will also print the results of a chi-squared analysis between the two subsets of cases.
[
{
"op":"and",
"content":[
{
"op":"=",
"content":{
"field":"cases.project.project_id",
"value":"TCGA-BRCA"
}
},
{
"op":"=",
"content":{
"field":"gene.ssm.ssm_id",
"value":"edd1ae2c-3ca9-52bd-a124-b09ed304fcc2"
}
}
]
},
{
"op":"and",
"content":[
{
"op":"=",
"content":{
"field":"cases.project.project_id",
"value":"TCGA-BRCA"
}
},
{
"op":"excludeifany",
"content":{
"field":"gene.ssm.ssm_id",
"value":"edd1ae2c-3ca9-52bd-a124-b09ed304fcc2"
}
}
]
}
]
curl "https://api.gdc.cancer.gov/analysis/survival?filters=%5B%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-BRCA%22%7D%7D%2C%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22gene.ssm.ssm_id%22%2C%22value%22%3A%22edd1ae2c-3ca9-52bd-a124-b09ed304fcc2%22%7D%7D%5D%7D%2C%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-BRCA%22%7D%7D%2C%7B%22op%22%3A%22excludeifany%22%2C%22content%22%3A%7B%22field%22%3A%22gene.ssm.ssm_id%22%2C%22value%22%3A%22edd1ae2c-3ca9-52bd-a124-b09ed304fcc2%22%7D%7D%5D%7D%5D&pretty=true"
{
"overallStats": {
"degreesFreedom": 1,
"chiSquared": 0.8577589072612264,
"pValue": 0.35436660628146011
},
"results": [
{
"donors": [
{
"survivalEstimate": 1,
"id": "a991644b-3ee6-4cda-acf0-e37de48a49fc",
"censored": true,
"time": 10
},
{
"survivalEstimate": 1,
"id": "2e1e3bf0-1708-4b65-936c-48b89eb8966a",
"censored": true,
"time": 19
},
(truncated)
],
"meta": {
"id": 140055251282040
}
},
{
"donors": [
{
"survivalEstimate": 1,
"id": "5e4187c9-98f8-4bdb-a8da-6a914e96f47a",
"censored": true,
"time": -31
},
(truncated)
The output represents two sets of coordinates delimited as objects with the donors tag. One set of coordinates will generate a survival plot representing TCGA-BRCA cases that have the mutation of interest and the other will generate a survival plot for the remaining cases in TCGA-BRCA.
Example 3: Custom survival plots can be generated using the GDC API. For example, a user could generate survival plot data comparing patients with a mutation in genes associated with a biological pathway with patients without mutations in that pathway. The following example compares a patient with at least one mutation in either gene ENSG00000141510 or ENSG00000155657 with patients that do not have mutations in these genes.
[
{
"op":"and",
"content":[
{
"op":"=",
"content":{
"field":"cases.project.project_id",
"value":"TCGA-BRCA"
}
},
{
"op":"=",
"content":{
"field":"gene.gene_id",
"value":["ENSG00000141510","ENSG00000155657"]
}
}
]
},
{
"op":"and",
"content":[
{
"op":"=",
"content":{
"field":"cases.project.project_id",
"value":"TCGA-BRCA"
}
},
{
"op":"excludeifany",
"content":{
"field":"gene.gene_id",
"value":["ENSG00000141510","ENSG00000155657"]
}
}
]
}
]
curl "https://api.gdc.cancer.gov/analysis/survival?filters=%5B%0D%0A%7B%0D%0A%22op%22%3A%22and%22%2C%0D%0A%22content%22%3A%5B%0D%0A%7B%0D%0A%22op%22%3A%22%3D%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22cases.project.project_id%22%2C%0D%0A%22value%22%3A%22TCGA-BRCA%22%0D%0A%7D%0D%0A%7D%2C%0D%0A%7B%0D%0A%22op%22%3A%22%3D%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22gene.gene_id%22%2C%0D%0A%22value%22%3A%5B%22ENSG00000141510%22%2C%22ENSG00000155657%22%5D%0D%0A%7D%0D%0A%7D%0D%0A%5D%0D%0A%7D%2C%0D%0A%7B%0D%0A%22op%22%3A%22and%22%2C%0D%0A%22content%22%3A%5B%0D%0A%7B%0D%0A%22op%22%3A%22%3D%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22cases.project.project_id%22%2C%0D%0A%22value%22%3A%22TCGA-BRCA%22%0D%0A%7D%0D%0A%7D%2C%0D%0A%7B%0D%0A%22op%22%3A%22excludeifany%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22gene.gene_id%22%2C%0D%0A%22value%22%3A%5B%22ENSG00000141510%22%2C%22ENSG00000155657%22%5D%0D%0A%7D%0D%0A%7D%0D%0A%5D%0D%0A%7D%0D%0A%5D&pretty=true"
Example 4: Survival plots can be even more customizable when sets of case IDs are used. Two sets of case IDs (or barcodes) can be retrieved in a separate step based on custom criteria and compared in a survival plot. See below for an example query.
[{
"op":"=",
"content":{
"field":"cases.submitter_id",
"value":["TCGA-HT-A74J","TCGA-43-A56U","TCGA-GM-A3XL","TCGA-A1-A0SQ","TCGA-K1-A6RV","TCGA-J2-A4AD","TCGA-XR-A8TE"]
}
},
{
"op":"=",
"content":{
"field":"cases.submitter_id",
"value":["TCGA-55-5899","TCGA-55-6642","TCGA-55-7907","TCGA-67-6216","TCGA-75-5146","TCGA-49-4510","TCGA-78-7159"]
}
}]
curl "https://api.gdc.cancer.gov/analysis/survival?filters=%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.submitter_id%22%2C%22value%22%3A%5B%22TCGA-HT-A74J%22%2C%22TCGA-43-A56U%22%2C%22TCGA-GM-A3XL%22%2C%22TCGA-A1-A0SQ%22%2C%22TCGA-K1-A6RV%22%2C%22TCGA-J2-A4AD%22%2C%22TCGA-XR-A8TE%22%5D%7D%7D%2C%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.submitter_id%22%2C%22value%22%3A%5B%22TCGA-55-5899%22%2C%22TCGA-55-6642%22%2C%22TCGA-55-7907%22%2C%22TCGA-67-6216%22%2C%22TCGA-75-5146%22%2C%22TCGA-49-4510%22%2C%22TCGA-78-7159%22%5D%7D%7D%5D"