"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"2022.10.24\n",
"\n"
],
"text/plain": [
"\u001b[1;36m2022.10\u001b[0m.\u001b[1;36m24\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from cdapython import Q, columns, unique_terms, query\n",
"import numpy as np\n",
"import pandas as pd\n",
"from itables import init_notebook_mode, show\n",
"init_notebook_mode(all_interactive=True)\n",
"import itables.options as opt\n",
"opt.maxBytes=0\n",
"opt.scrollX=\"200px\"\n",
"opt.scrollCollapse=True\n",
"opt.paging=True\n",
"opt.maxColumns=0\n",
"print(Q.get_version())"
]
},
{
"cell_type": "markdown",
"id": "d538da92",
"metadata": {},
"source": [
"\n",
" \n",
"CDA data comes from three sources:\n",
"
\n",
" \n",
"The CDA makes this data searchable in four main endpoints:\n",
"\n",
"
\n",
"- subject: A patient entity captures the study-independent metadata for research subjects. Human research subjects are usually not traceable to a particular person to protect the subjects privacy.
\n",
"- researchsubject: A research subject is the entity of interest in a specific research study or project, typically a human being or an animal, but can also be a device, group of humans or animals, or a tissue sample. Human research subjects are usually not traceable to a particular person to protect the subjects privacy. This entity plays the role of the case_id in existing data. A subject who participates in 3 studies will have 3 researchsubject IDs.
\n",
"- specimen: Any material taken as a sample from a biological entity (living or dead), or from a physical object or the environment. Specimens are usually collected as an example of their kind, often for use in some investigation.
\n",
"- mutation: Molecular data about specific mutations, currently limited to the TCGA-READ project from GDC.
\n",
"
\n",
"one endpoint that can be added to the subject, researchsubject, or specimen to get the relevant files: \n",
"
\n",
"- file: A unit of data about subjects, researchsubjects, specimens, or their associated information.
\n",
"
\n",
"and two endpoints that offer deeper information about data in the researchsubject endpoint:\n",
"
\n",
"- diagnosis: A collection of characteristics that describe an abnormal condition of the body as assessed at a point in time. May be used to capture information about neoplastic and non-neoplastic conditions.
\n",
"- treatment: Represent medication administration or other treatment types.
\n",
"
\n",
"
\n",
"
Where did those terms come from?
\n",
" \n",
"If you aren't sure how we knew what terms to put in our search, please refer back to the
What search terms are available? notebook. \n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 10.88 sec 10880 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m10.88\u001b[0m sec \u001b[1;36m10880\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"specimen_count : 39220\n",
"\n"
],
"text/plain": [
"specimen_count : \u001b[1;36m39220\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"treatment_count : 2396\n",
"\n"
],
"text/plain": [
"treatment_count : \u001b[1;36m2396\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"diagnosis_count : 1757\n",
"\n"
],
"text/plain": [
"diagnosis_count : \u001b[1;36m1757\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"mutation_count : 904\n",
"\n"
],
"text/plain": [
"mutation_count : \u001b[1;36m904\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"researchsubject_count : 4347\n",
"\n"
],
"text/plain": [
"researchsubject_count : \u001b[1;36m4347\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"subject_count : 3015\n",
"\n"
],
"text/plain": [
"subject_count : \u001b[1;36m3015\u001b[0m\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": []
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.count.run()"
]
},
{
"cell_type": "markdown",
"id": "d483e944",
"metadata": {},
"source": [
"These numbers are how many total rows of data will come back when querying the various endpoints.\n",
"\n",
"\n",
"\n",
"### subject summary\n",
"\n",
"We can also add `count`to the other run calls we did in the Basic Search notebook to get more detailed summaries:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "6d9137aa",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 13.584 sec 13584 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m13.584\u001b[0m sec \u001b[1;36m13584\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"subjectresults = myquery.subject.count.run()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "4d0501a2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 3.911 sec 3911 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m3.911\u001b[0m sec \u001b[1;36m3911\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" files : 4924982 \n",
"\n"
],
"text/plain": [
" files : \u001b[1;36m4924982\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 3015 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m3015\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | sex | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | female | \n",
" 653 | \n",
"
\n",
" \n",
" | male | \n",
" 981 | \n",
"
\n",
" \n",
" | not reported | \n",
" 3 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | race | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | not reported | \n",
" 136 | \n",
"
\n",
" \n",
" | white | \n",
" 1312 | \n",
"
\n",
" \n",
" | black or african american | \n",
" 96 | \n",
"
\n",
" \n",
" | asian | \n",
" 33 | \n",
"
\n",
" \n",
" | american indian or alaska native | \n",
" 4 | \n",
"
\n",
" \n",
" | not allowed to collect | \n",
" 25 | \n",
"
\n",
" \n",
" | other | \n",
" 9 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 21 | \n",
"
\n",
" \n",
" | native hawaiian or other pacific islander | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | ethnicity | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | not hispanic or latino | \n",
" 1286 | \n",
"
\n",
" \n",
" | not reported | \n",
" 219 | \n",
"
\n",
" \n",
" | hispanic or latino | \n",
" 85 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 22 | \n",
"
\n",
" \n",
" | not allowed to collect | \n",
" 25 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | cause_of_death | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 2746 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 199 | \n",
"
\n",
" \n",
" | Not Cancer Related | \n",
" 9 | \n",
"
\n",
" \n",
" | Cancer Related | \n",
" 48 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 8 | \n",
"
\n",
" \n",
" | Infection | \n",
" 3 | \n",
"
\n",
" \n",
" | Surgical Complications | \n",
" 2 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | subject_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | IDC | \n",
" 2585 | \n",
"
\n",
" \n",
" | PDC | \n",
" 309 | \n",
"
\n",
" \n",
" | GDC | \n",
" 1455 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.subject.count.run()"
]
},
{
"cell_type": "markdown",
"id": "dff2da08",
"metadata": {},
"source": [
"Since we save the output as a variable, we need to look at the variable to see the results:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "993479db",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
" files : 4924982 \n",
"\n"
],
"text/plain": [
" files : \u001b[1;36m4924982\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 3015 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m3015\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | sex | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | female | \n",
" 653 | \n",
"
\n",
" \n",
" | male | \n",
" 981 | \n",
"
\n",
" \n",
" | not reported | \n",
" 3 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | race | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | not reported | \n",
" 136 | \n",
"
\n",
" \n",
" | white | \n",
" 1312 | \n",
"
\n",
" \n",
" | black or african american | \n",
" 96 | \n",
"
\n",
" \n",
" | asian | \n",
" 33 | \n",
"
\n",
" \n",
" | american indian or alaska native | \n",
" 4 | \n",
"
\n",
" \n",
" | not allowed to collect | \n",
" 25 | \n",
"
\n",
" \n",
" | other | \n",
" 9 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 21 | \n",
"
\n",
" \n",
" | native hawaiian or other pacific islander | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | ethnicity | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1378 | \n",
"
\n",
" \n",
" | not hispanic or latino | \n",
" 1286 | \n",
"
\n",
" \n",
" | not reported | \n",
" 219 | \n",
"
\n",
" \n",
" | hispanic or latino | \n",
" 85 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 22 | \n",
"
\n",
" \n",
" | not allowed to collect | \n",
" 25 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | cause_of_death | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 2746 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 199 | \n",
"
\n",
" \n",
" | Not Cancer Related | \n",
" 9 | \n",
"
\n",
" \n",
" | Cancer Related | \n",
" 48 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 8 | \n",
"
\n",
" \n",
" | Infection | \n",
" 3 | \n",
"
\n",
" \n",
" | Surgical Complications | \n",
" 2 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | subject_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | IDC | \n",
" 2585 | \n",
"
\n",
" \n",
" | PDC | \n",
" 309 | \n",
"
\n",
" \n",
" | GDC | \n",
" 1455 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"subjectresults"
]
},
{
"cell_type": "markdown",
"id": "e7e6d522",
"metadata": {},
"source": [
"By default, the results are displayed as a table for easy previewing of the data. Since we queried the `subject` endpoint, our default results tell us `subject` level information, that is, information about unique individuals: their sex, race, age, species, etc. Using counts gives us back a nice pivot table type summary of the countable fields for Subjects. Note that above the table it also tells you the total subject count, as well as how many files are associated with those subjects."
]
},
{
"cell_type": "markdown",
"id": "05e52f3f",
"metadata": {},
"source": [
"\n",
"---\n",
"\n",
"\n",
"\n",
"
Subject Field Definitions
\n",
"\n",
"
A patient entity captures the study-independent metadata for research subjects. Human research subjects are usually not traceable to a particular person to protect the subjects privacy.\n",
" \n",
" \n",
" \n",
"\n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of subjects returned. | \n",
"
\n",
" \n",
" | files | \n",
" The number of files that match this search. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | species | \n",
" The taxonomic group (e.g. species) of the subject. | \n",
"
\n",
" \n",
" | sex | \n",
" The biologic character or quality that distinguishes male and female from one another as expressed by analysis of the person's gonadal, morphologic (internal and external), chromosomal, and hormonal characteristics. | \n",
"
\n",
" \n",
" | race | \n",
" An arbitrary classification of a taxonomic group that is a division of a species. | \n",
"
\n",
" \n",
" | ethnicity | \n",
" An individual's self-described social and cultural grouping. | \n",
"
\n",
" \n",
" | cause_of_death | \n",
" The cause of death, if known | \n",
"
\n",
"\n",
"
\n",
"\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 11.082 sec 11082 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m11.082\u001b[0m sec \u001b[1;36m11082\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" files : 4924962 \n",
"\n"
],
"text/plain": [
" files : \u001b[1;36m4924962\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 4347 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m4347\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | primary_diagnosis_condition | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Gliomas | \n",
" 1247 | \n",
"
\n",
" \n",
" | Glioblastoma | \n",
" 100 | \n",
"
\n",
" \n",
" | Germ Cell Neoplasms | \n",
" 104 | \n",
"
\n",
" \n",
" | None | \n",
" 2583 | \n",
"
\n",
" \n",
" | Pediatric/AYA Brain Tumors | \n",
" 199 | \n",
"
\n",
" \n",
" | Not Applicable | \n",
" 9 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 11 | \n",
"
\n",
" \n",
" | Malignant Lymphomas, NOS or Diffuse | \n",
" 14 | \n",
"
\n",
" \n",
" | Neoplasms, NOS | \n",
" 66 | \n",
"
\n",
" \n",
" | Other | \n",
" 10 | \n",
"
\n",
" \n",
" | Neuroepitheliomatous Neoplasms | \n",
" 2 | \n",
"
\n",
" \n",
" | Mature B-Cell Lymphomas | \n",
" 2 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | primary_diagnosis_site | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Brain | \n",
" 4347 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | researchsubject_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | GDC | \n",
" 1455 | \n",
"
\n",
" \n",
" | PDC | \n",
" 309 | \n",
"
\n",
" \n",
" | IDC | \n",
" 2583 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.researchsubject.count.run()"
]
},
{
"cell_type": "markdown",
"id": "4564beee",
"metadata": {},
"source": [
"\n",
"\n",
"\n",
"---\n",
"\n",
"\n",
"\n",
"
ResearchSubject Field Definitions
\n",
"\n",
"
A research subject is the entity of interest in a specific research study or project, typically a human being or an animal, but can also be a device, group of humans or animals, or a tissue sample. Human research subjects are usually not traceable to a particular person to protect the subjects privacy. This entity plays the role of the case_id in existing data. An individual who participates in 3 studies will have 3 researchsubject IDs\n",
" \n",
"\n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of researchsubjects returned. | \n",
"
\n",
" \n",
" | files | \n",
" The number of files that match this search. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | primary_diagnosis_condition | \n",
" The text term used to describe the type of malignant disease. | \n",
"
\n",
" \n",
" | primary_diagnosis_site | \n",
" The text term used to describe the primary site of disease. | \n",
"
\n",
"\n",
"
\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 4.961 sec 4961 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m4.961\u001b[0m sec \u001b[1;36m4961\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 1757 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m1757\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | primary_diagnosis | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Glioblastoma | \n",
" 822 | \n",
"
\n",
" \n",
" | Mixed glioma | \n",
" 131 | \n",
"
\n",
" \n",
" | Oligodendroglioma, NOS | \n",
" 112 | \n",
"
\n",
" \n",
" | Astrocytoma, anaplastic | \n",
" 130 | \n",
"
\n",
" \n",
" | Ganglioglioma, NOS | \n",
" 18 | \n",
"
\n",
" \n",
" | Astrocytoma, NOS | \n",
" 64 | \n",
"
\n",
" \n",
" | Ependymoma, NOS | \n",
" 32 | \n",
"
\n",
" \n",
" | Mixed germ cell tumor | \n",
" 79 | \n",
"
\n",
" \n",
" | Glioma, NOS | \n",
" 93 | \n",
"
\n",
" \n",
" | Neoplasm, uncertain whether benign or malignant | \n",
" 13 | \n",
"
\n",
" \n",
" | Oligodendroglioma, anaplastic | \n",
" 78 | \n",
"
\n",
" \n",
" | Malignant lymphoma, NOS | \n",
" 14 | \n",
"
\n",
" \n",
" | Teratoma, benign | \n",
" 3 | \n",
"
\n",
" \n",
" | Neoplasm, malignant | \n",
" 50 | \n",
"
\n",
" \n",
" | Embryonal carcinoma, NOS | \n",
" 8 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 10 | \n",
"
\n",
" \n",
" | Craniopharyngioma | \n",
" 16 | \n",
"
\n",
" \n",
" | Germinoma | \n",
" 4 | \n",
"
\n",
" \n",
" | Glioma, malignant | \n",
" 26 | \n",
"
\n",
" \n",
" | Medulloblastoma, NOS | \n",
" 22 | \n",
"
\n",
" \n",
" | Yolk sac tumor | \n",
" 8 | \n",
"
\n",
" \n",
" | Malignant lymphoma, large B-cell, diffuse, NOS | \n",
" 2 | \n",
"
\n",
" \n",
" | Atypical teratoid/rhabdoid tumor | \n",
" 12 | \n",
"
\n",
" \n",
" | Glioblastoma multiforme | \n",
" 4 | \n",
"
\n",
" \n",
" | Teratoma, malignant, NOS | \n",
" 2 | \n",
"
\n",
" \n",
" | Gliosarcoma | \n",
" 1 | \n",
"
\n",
" \n",
" | Oligoastrocytoma | \n",
" 1 | \n",
"
\n",
" \n",
" | Papillary glioneuronal tumor | \n",
" 2 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | stage | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 1428 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 110 | \n",
"
\n",
" \n",
" | Unknown | \n",
" 219 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | grade | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | not reported | \n",
" 1116 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 392 | \n",
"
\n",
" \n",
" | None | \n",
" 28 | \n",
"
\n",
" \n",
" | High Grade | \n",
" 26 | \n",
"
\n",
" \n",
" | G1 | \n",
" 98 | \n",
"
\n",
" \n",
" | G4 | \n",
" 36 | \n",
"
\n",
" \n",
" | G2 | \n",
" 52 | \n",
"
\n",
" \n",
" | Low Grade | \n",
" 9 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | diagnosis_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | GDC | \n",
" 1428 | \n",
"
\n",
" \n",
" | PDC | \n",
" 329 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.diagnosis.count.run()"
]
},
{
"cell_type": "markdown",
"id": "eb73357c",
"metadata": {},
"source": [
"---\n",
"\n",
"\n",
"\n",
"
Diagnosis Field Definitions
\n",
"\n",
"
A collection of characteristics that describe an abnormal condition of the body as assessed at a point in time. May be used to capture information about neoplastic and non-neoplastic conditions.\n",
"\n",
"\n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of diagnoses returned. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | primary_diagnosis | \n",
" The diagnosis instance that qualified a subject for inclusion on a ResearchProject. | \n",
"
\n",
" \n",
" | stage | \n",
" The extent of a cancer in the body. | \n",
"
\n",
" \n",
" | grade | \n",
" The degree of abnormality of cancer cells. | \n",
"
\n",
"\n",
"
\n",
"\n",
"\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 4.906 sec 4906 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m4.906\u001b[0m sec \u001b[1;36m4906\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 2396 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m2396\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | treatment_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 2396 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | treatment_effect | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 2396 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | treatment_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | GDC | \n",
" 2396 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.treatment.count.run()"
]
},
{
"cell_type": "markdown",
"id": "ec5dda7f",
"metadata": {},
"source": [
"\n",
"---\n",
"\n",
"\n",
"\n",
"
Treatment Field Definitions
\n",
"\n",
"
Medication administration or other treatment types. A single research subject may have multiple treatments for a single diagnosis, and/or different diagnoses, and different treatments, across different studies\n",
" \n",
"\n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of treatments returned. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | treatment_type | \n",
" The treatment type including medication/therapeutics or other procedures. | \n",
"
\n",
" \n",
" | treatment_effect | \n",
" The effect of a treatment on the diagnosis or tumor. | \n",
"
\n",
"\n",
"
\n",
" \n",
"\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 11.052 sec 11052 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m11.052\u001b[0m sec \u001b[1;36m11052\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" files : 47327 \n",
"\n"
],
"text/plain": [
" files : \u001b[1;36m47327\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 39220 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m39220\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | primary_disease_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Gliomas | \n",
" 37586 | \n",
"
\n",
" \n",
" | Glioblastoma | \n",
" 200 | \n",
"
\n",
" \n",
" | Not Applicable | \n",
" 36 | \n",
"
\n",
" \n",
" | Germ Cell Neoplasms | \n",
" 416 | \n",
"
\n",
" \n",
" | Pediatric/AYA Brain Tumors | \n",
" 438 | \n",
"
\n",
" \n",
" | Neoplasms, NOS | \n",
" 285 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 121 | \n",
"
\n",
" \n",
" | Mature B-Cell Lymphomas | \n",
" 54 | \n",
"
\n",
" \n",
" | Malignant Lymphomas, NOS or Diffuse | \n",
" 56 | \n",
"
\n",
" \n",
" | Other | \n",
" 20 | \n",
"
\n",
" \n",
" | Neuroepitheliomatous Neoplasms | \n",
" 8 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | source_material_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Primary Tumor | \n",
" 27578 | \n",
"
\n",
" \n",
" | Metastatic | \n",
" 252 | \n",
"
\n",
" \n",
" | Solid Tissue Normal | \n",
" 538 | \n",
"
\n",
" \n",
" | Blood Derived Normal | \n",
" 10078 | \n",
"
\n",
" \n",
" | Recurrent Tumor | \n",
" 513 | \n",
"
\n",
" \n",
" | Buccal Cell Normal | \n",
" 14 | \n",
"
\n",
" \n",
" | Next Generation Cancer Model | \n",
" 176 | \n",
"
\n",
" \n",
" | Expanded Next Generation Cancer Model | \n",
" 35 | \n",
"
\n",
" \n",
" | Not Reported | \n",
" 36 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | specimen_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | aliquot | \n",
" 18701 | \n",
"
\n",
" \n",
" | analyte | \n",
" 6676 | \n",
"
\n",
" \n",
" | portion | \n",
" 5996 | \n",
"
\n",
" \n",
" | slide | \n",
" 3754 | \n",
"
\n",
" \n",
" | sample | \n",
" 4093 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | specimen_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | GDC | \n",
" 38562 | \n",
"
\n",
" \n",
" | PDC | \n",
" 658 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.specimen.count.run()"
]
},
{
"cell_type": "markdown",
"id": "7f254547",
"metadata": {},
"source": [
"Nearly 40,000 specimens with over 50,000 files meet our search criteria! We would typically expect this number to be much larger than our number of subjects or research_subjects. First because studies will often take more than one sample per subject, and second because any given specimen might be aliquoted out to be used in multiple tests. "
]
},
{
"cell_type": "markdown",
"id": "b3ed75e5",
"metadata": {},
"source": [
"\n",
"\n",
"
Specimen Field Definitions
\n",
"\n",
"
Any material taken as a sample from a biological entity (living or dead), or from a physical object or the environment. Specimens are usually collected as an example of their kind, often for use in some investigation.\n",
" A given specimen will have only a single subject ID and a single research subject ID\n",
" \n",
" \n",
"\n",
" \n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of specimens returned. | \n",
"
\n",
" \n",
" | files | \n",
" The number of files that match this search. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | primary_disease_type | \n",
" The text term used to describe the type of malignant disease. | \n",
"
\n",
" \n",
" | source_material_type | \n",
" The general kind of material from which the specimen was derived. | \n",
"
\n",
" \n",
" | specimen_type | \n",
" The high-level type of the specimen, based on its how it has been derived from the original extracted sample. One of: analyte, aliquot, portion, sample, or slide. | \n",
"
\n",
"\n",
"
\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 13.645 sec 13645 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m13.645\u001b[0m sec \u001b[1;36m13645\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
" total : 4924982 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m4924982\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | data_category | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Imaging | \n",
" 4874560 | \n",
"
\n",
" \n",
" | Simple Nucleotide Variation | \n",
" 16970 | \n",
"
\n",
" \n",
" | Peptide Spectral Matches | \n",
" 1524 | \n",
"
\n",
" \n",
" | DNA Methylation | \n",
" 3342 | \n",
"
\n",
" \n",
" | Copy Number Variation | \n",
" 6913 | \n",
"
\n",
" \n",
" | Structural Variation | \n",
" 3384 | \n",
"
\n",
" \n",
" | Sequencing Reads | \n",
" 5897 | \n",
"
\n",
" \n",
" | Raw Mass Spectra | \n",
" 762 | \n",
"
\n",
" \n",
" | Processed Mass Spectra | \n",
" 762 | \n",
"
\n",
" \n",
" | Biospecimen | \n",
" 5583 | \n",
"
\n",
" \n",
" | Proteome Profiling | \n",
" 679 | \n",
"
\n",
" \n",
" | Transcriptome Profiling | \n",
" 3116 | \n",
"
\n",
" \n",
" | Clinical | \n",
" 1187 | \n",
"
\n",
" \n",
" | Somatic Structural Variation | \n",
" 303 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | data_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | None | \n",
" 4874560 | \n",
"
\n",
" \n",
" | Aligned Reads | \n",
" 5897 | \n",
"
\n",
" \n",
" | Text | \n",
" 762 | \n",
"
\n",
" \n",
" | Raw Simple Somatic Mutation | \n",
" 5033 | \n",
"
\n",
" \n",
" | Clinical Supplement | \n",
" 1182 | \n",
"
\n",
" \n",
" | Transcript Fusion | \n",
" 3385 | \n",
"
\n",
" \n",
" | Slide Image | \n",
" 3629 | \n",
"
\n",
" \n",
" | Masked Somatic Mutation | \n",
" 1146 | \n",
"
\n",
" \n",
" | Gene Level Copy Number | \n",
" 1222 | \n",
"
\n",
" \n",
" | Masked Copy Number Segment | \n",
" 2185 | \n",
"
\n",
" \n",
" | Proprietary | \n",
" 762 | \n",
"
\n",
" \n",
" | Annotated Somatic Mutation | \n",
" 9462 | \n",
"
\n",
" \n",
" | Biospecimen Supplement | \n",
" 1954 | \n",
"
\n",
" \n",
" | Aggregated Somatic Mutation | \n",
" 1146 | \n",
"
\n",
" \n",
" | Open Standard | \n",
" 1524 | \n",
"
\n",
" \n",
" | Copy Number Segment | \n",
" 2336 | \n",
"
\n",
" \n",
" | Masked Intensities | \n",
" 2228 | \n",
"
\n",
" \n",
" | Allele-specific Copy Number Segment | \n",
" 1071 | \n",
"
\n",
" \n",
" | Methylation Beta Value | \n",
" 1114 | \n",
"
\n",
" \n",
" | Gene Expression Quantification | \n",
" 906 | \n",
"
\n",
" \n",
" | Structural Rearrangement | \n",
" 302 | \n",
"
\n",
" \n",
" | Splice Junction Quantification | \n",
" 870 | \n",
"
\n",
" \n",
" | Protein Expression Quantification | \n",
" 679 | \n",
"
\n",
" \n",
" | miRNA Expression Quantification | \n",
" 643 | \n",
"
\n",
" \n",
" | Gene Level Copy Number Scores | \n",
" 99 | \n",
"
\n",
" \n",
" | Isoform Expression Quantification | \n",
" 643 | \n",
"
\n",
" \n",
" | Masked Annotated Somatic Mutation | \n",
" 183 | \n",
"
\n",
" \n",
" | Single Cell Analysis | \n",
" 36 | \n",
"
\n",
" \n",
" | Differential Gene Expression | \n",
" 18 | \n",
"
\n",
" \n",
" | Pathology Report | \n",
" 5 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | file_format | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | DICOM | \n",
" 4874560 | \n",
"
\n",
" \n",
" | vendor-specific | \n",
" 762 | \n",
"
\n",
" \n",
" | mzML | \n",
" 762 | \n",
"
\n",
" \n",
" | BAM | \n",
" 5897 | \n",
"
\n",
" \n",
" | BCR Biotab | \n",
" 49 | \n",
"
\n",
" \n",
" | TXT | \n",
" 8851 | \n",
"
\n",
" \n",
" | tsv | \n",
" 762 | \n",
"
\n",
" \n",
" | VCF | \n",
" 9915 | \n",
"
\n",
" \n",
" | TSV | \n",
" 4561 | \n",
"
\n",
" \n",
" | MAF | \n",
" 7206 | \n",
"
\n",
" \n",
" | mzIdentML | \n",
" 762 | \n",
"
\n",
" \n",
" | IDAT | \n",
" 2228 | \n",
"
\n",
" \n",
" | BCR XML | \n",
" 2282 | \n",
"
\n",
" \n",
" | SVS | \n",
" 3629 | \n",
"
\n",
" \n",
" | BEDPE | \n",
" 1892 | \n",
"
\n",
" \n",
" | MEX | \n",
" 36 | \n",
"
\n",
" \n",
" | BCR SSF XML | \n",
" 758 | \n",
"
\n",
" \n",
" | HDF5 | \n",
" 18 | \n",
"
\n",
" \n",
" | BCR OMF XML | \n",
" 19 | \n",
"
\n",
" \n",
" | CDC JSON | \n",
" 28 | \n",
"
\n",
" \n",
" | PDF | \n",
" 5 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | file_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | IDC | \n",
" 4874560 | \n",
"
\n",
" \n",
" | PDC | \n",
" 3048 | \n",
"
\n",
" \n",
" | GDC | \n",
" 47374 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.file.count.run()"
]
},
{
"cell_type": "markdown",
"id": "e34044c9",
"metadata": {},
"source": [
"There are a huge number of files (4099497) that match our search. Likely we would want to additionally filter the results by file format or data type to get only files we can use. See all the ways you can filter and refine searches with more search terms in the Operators notebook.\n",
"\n",
"\n",
"\n",
"\n",
"
File Field Definitions
\n",
"\n",
"
A file is an information-bearing electronic object that contains a physical embodiment of some information using a particular character encoding.\n",
"\n",
" \n",
"\n",
"
\n",
"\n",
" \n",
" | id (`total`) | \n",
" The overall number of files returned. | \n",
"
\n",
" \n",
" | identifier.value(`system`) | \n",
" The identifier for the data provider. | \n",
"
\n",
" \n",
" | data_catagory | \n",
" Broad categorization of the contents of the data file. | \n",
"
\n",
" \n",
" | data_type | \n",
" Specific content type of the data file. | \n",
"
\n",
" \n",
" | file_format | \n",
" Format of the data files. | \n",
"
\n",
"\n",
"
\n",
"\n",
"
Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Http Status: 500\n",
" Error Message: Unrecognized name: case_barcode at [1:770]\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Http Status: \u001b[1;36m500\u001b[0m\n",
" Error Message: Unrecognized name: case_barcode at \u001b[1m[\u001b[0m\u001b[1;92m1:770\u001b[0m\u001b[1m]\u001b[0m\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 1.129 sec 1129 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m1.129\u001b[0m sec \u001b[1;36m1129\u001b[0m ms\n",
" \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"myquery.mutation.count.run()"
]
},
{
"cell_type": "markdown",
"id": "6a4fd46e",
"metadata": {},
"source": [
"## Files from a single endpoint (endpoint chaining)\n",
"\n",
"If you want all file formats and data types, but only from a specific endpoint, you can also filter the file results by chaining endpoints together. This will return all the files that match our search AND that are specifically from specimens:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "2cfb2582",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"Getting results from database\n",
"\n",
"\n"
],
"text/plain": [
"Getting results from database\n",
"\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"\n",
" Total execution time: 0\n",
" min 10.612 sec 10612 ms\n",
" \n",
"\n"
],
"text/plain": [
"\n",
" Total execution time: \u001b[1;36m0\u001b[0m\n",
" min \u001b[1;36m10.612\u001b[0m sec \u001b[1;36m10612\u001b[0m ms\n",
" \n"
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},
"metadata": {},
"output_type": "display_data"
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{
"data": {
"text/html": [
" total : 47327 \n",
"\n"
],
"text/plain": [
" total : \u001b[1;36m47327\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
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{
"data": {
"text/html": [
"\n",
"\n",
" \n",
" \n",
" | data_category | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Simple Nucleotide Variation | \n",
" 16970 | \n",
"
\n",
" \n",
" | Copy Number Variation | \n",
" 6959 | \n",
"
\n",
" \n",
" | Processed Mass Spectra | \n",
" 762 | \n",
"
\n",
" \n",
" | DNA Methylation | \n",
" 3342 | \n",
"
\n",
" \n",
" | Peptide Spectral Matches | \n",
" 1524 | \n",
"
\n",
" \n",
" | Biospecimen | \n",
" 3629 | \n",
"
\n",
" \n",
" | Transcriptome Profiling | \n",
" 3116 | \n",
"
\n",
" \n",
" | Raw Mass Spectra | \n",
" 762 | \n",
"
\n",
" \n",
" | Sequencing Reads | \n",
" 5897 | \n",
"
\n",
" \n",
" | Structural Variation | \n",
" 3384 | \n",
"
\n",
" \n",
" | Proteome Profiling | \n",
" 679 | \n",
"
\n",
" \n",
" | Somatic Structural Variation | \n",
" 303 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | data_type | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | Masked Copy Number Segment | \n",
" 2231 | \n",
"
\n",
" \n",
" | Slide Image | \n",
" 3629 | \n",
"
\n",
" \n",
" | Open Standard | \n",
" 1524 | \n",
"
\n",
" \n",
" | Text | \n",
" 762 | \n",
"
\n",
" \n",
" | Aggregated Somatic Mutation | \n",
" 1146 | \n",
"
\n",
" \n",
" | Proprietary | \n",
" 762 | \n",
"
\n",
" \n",
" | Raw Simple Somatic Mutation | \n",
" 5033 | \n",
"
\n",
" \n",
" | Masked Intensities | \n",
" 2228 | \n",
"
\n",
" \n",
" | Transcript Fusion | \n",
" 3385 | \n",
"
\n",
" \n",
" | Aligned Reads | \n",
" 5897 | \n",
"
\n",
" \n",
" | Masked Somatic Mutation | \n",
" 1146 | \n",
"
\n",
" \n",
" | Copy Number Segment | \n",
" 2336 | \n",
"
\n",
" \n",
" | Annotated Somatic Mutation | \n",
" 9462 | \n",
"
\n",
" \n",
" | Methylation Beta Value | \n",
" 1114 | \n",
"
\n",
" \n",
" | Gene Level Copy Number | \n",
" 1222 | \n",
"
\n",
" \n",
" | Isoform Expression Quantification | \n",
" 643 | \n",
"
\n",
" \n",
" | Gene Expression Quantification | \n",
" 906 | \n",
"
\n",
" \n",
" | miRNA Expression Quantification | \n",
" 643 | \n",
"
\n",
" \n",
" | Masked Annotated Somatic Mutation | \n",
" 183 | \n",
"
\n",
" \n",
" | Gene Level Copy Number Scores | \n",
" 99 | \n",
"
\n",
" \n",
" | Splice Junction Quantification | \n",
" 870 | \n",
"
\n",
" \n",
" | Allele-specific Copy Number Segment | \n",
" 1071 | \n",
"
\n",
" \n",
" | Protein Expression Quantification | \n",
" 679 | \n",
"
\n",
" \n",
" | Structural Rearrangement | \n",
" 302 | \n",
"
\n",
" \n",
" | Single Cell Analysis | \n",
" 36 | \n",
"
\n",
" \n",
" | Differential Gene Expression | \n",
" 18 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | file_format | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | TXT | \n",
" 8897 | \n",
"
\n",
" \n",
" | MAF | \n",
" 7206 | \n",
"
\n",
" \n",
" | tsv | \n",
" 762 | \n",
"
\n",
" \n",
" | SVS | \n",
" 3629 | \n",
"
\n",
" \n",
" | TSV | \n",
" 4561 | \n",
"
\n",
" \n",
" | VCF | \n",
" 9915 | \n",
"
\n",
" \n",
" | mzIdentML | \n",
" 762 | \n",
"
\n",
" \n",
" | BAM | \n",
" 5897 | \n",
"
\n",
" \n",
" | vendor-specific | \n",
" 762 | \n",
"
\n",
" \n",
" | mzML | \n",
" 762 | \n",
"
\n",
" \n",
" | BEDPE | \n",
" 1892 | \n",
"
\n",
" \n",
" | IDAT | \n",
" 2228 | \n",
"
\n",
" \n",
" | MEX | \n",
" 36 | \n",
"
\n",
" \n",
" | HDF5 | \n",
" 18 | \n",
"
\n",
" \n",
"
\n",
"\n",
"\n",
" \n",
" \n",
" | file_identifier_system | \n",
" count | \n",
"
\n",
" \n",
" \n",
" \n",
" | GDC | \n",
" 44279 | \n",
"
\n",
" \n",
" | PDC | \n",
" 3048 | \n",
"
\n",
" \n",
"
\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"myquery.specimen.file.count.run()"
]
},
{
"cell_type": "markdown",
"id": "6994e312",
"metadata": {},
"source": [
"Learn more about chaining endpoints in the [Chaining endpoints](\"../AdvancedSearch-Chaining\") notebook."
]
}
],
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