{"__v":0,"_id":"584593e448293d1900d1fc0c","category":{"project":"55faf11ba62ba1170021a9a7","version":"55faf11ba62ba1170021a9aa","_id":"58458b4fba4f1c0f009692bb","__v":0,"sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-12-05T15:44:15.650Z","from_sync":false,"order":6,"slug":"datasets-hub","title":"DATASETS HUB"},"parentDoc":null,"project":"55faf11ba62ba1170021a9a7","user":"5613e4f8fdd08f2b00437620","version":{"__v":35,"_id":"55faf11ba62ba1170021a9aa","project":"55faf11ba62ba1170021a9a7","createdAt":"2015-09-17T16:58:03.490Z","releaseDate":"2015-09-17T16:58:03.490Z","categories":["55faf11ca62ba1170021a9ab","55faf8f4d0e22017005b8272","55faf91aa62ba1170021a9b5","55faf929a8a7770d00c2c0bd","55faf932a8a7770d00c2c0bf","55faf94b17b9d00d00969f47","55faf958d0e22017005b8274","55faf95fa8a7770d00c2c0c0","55faf96917b9d00d00969f48","55faf970a8a7770d00c2c0c1","55faf98c825d5f19001fa3a6","55faf99aa62ba1170021a9b8","55faf99fa62ba1170021a9b9","55faf9aa17b9d00d00969f49","55faf9b6a8a7770d00c2c0c3","55faf9bda62ba1170021a9ba","5604570090ee490d00440551","5637e8b2fbe1c50d008cb078","5649bb624fa1460d00780add","5671974d1b6b730d008b4823","5671979d60c8e70d006c9760","568e8eef70ca1f0d0035808e","56d0a2081ecc471500f1795e","56d4a0adde40c70b00823ea3","56d96b03dd90610b00270849","56fbb83d8f21c817002af880","573c811bee2b3b2200422be1","576bc92afb62dd20001cda85","5771811e27a5c20e00030dcd","5785191af3a10c0e009b75b0","57bdf84d5d48411900cd8dc0","57ff5c5dc135231700aed806","5804caf792398f0f00e77521","58458b4fba4f1c0f009692bb","586d3c287c6b5b2300c05055"],"is_deprecated":false,"is_hidden":false,"is_beta":true,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"updates":[],"next":{"pages":[],"description":""},"createdAt":"2016-12-05T16:20:52.483Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":19,"body":"[block:callout]\n{\n  \"type\": \"warning\",\n  \"title\": \"On this page:\",\n  \"body\": \"[Overview](#section-overview)\\n[Anatomy of a query](#section-anatomy-of-a-query)\\n[Start from an entity](#section-start-from-an-entity)\\n[Filter by an entity's properties](#section-filter-by-an-entity-s-properties)\\n[View results in the table](#section-view-results-in-the-table)\\n[Access data for use in your project](#section-access-data-for-use-in-your-project)\\n[Example: build a query](#section-example-build-a-query)\\n[Objective](#section-objective)\\n[Procedure](#section-procedure)\"\n}\n[/block]\n##Overview\n\nBuild your own queries from scratch using the metadata associated with each dataset. Metadata consists of properties, which describe each dataset’s entities, and their values. Entities are particular resources with UUIDs, such as files, cases, samples, and cell lines. Learn more [about metadata for datasets](about-metadata-for-datasets).\n\nOn this page, learn about the [parts of a query](#section-anatomy-of-a-query). Then, walk through an example demonstrating [building a query from scratch](#section-example-build-a-query).\n\n<div align=\"right\"><a href=\"#top\">top</a></div>\n\n##Anatomy of a query\n###Start from an entity\n\nThe entities of each dataset are displayed on the Data Browser when you first open it, as shown below. Start your queries from a dataset's entities. Simply click on an entity, such as **Case** below, to start.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/3ebb971-c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg\",\n        \"c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg\",\n        1974,\n        1326,\n        \"#3e756e\"\n      ]\n    }\n  ]\n}\n[/block]\nAdd additional entities by clicking on a previously added entity. A list of entities associated with the first one appears, as shown below. For instance, a **Case** can have associated **Files** (about the case), **Samples** (taken from the patient), and **Drug therapies** (given to the patient). Hover over an entity for more information.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/22b4a2d-HHcEiAHQZGeSZc1ra23l_Screen_Shot_2016-06-10_at_3.58.33_PM_2_copy_1.jpg\",\n        \"HHcEiAHQZGeSZc1ra23l_Screen Shot 2016-06-10 at 3.58.33 PM (2) copy (1).jpg\",\n        718,\n        445,\n        \"#426d75\"\n      ]\n    }\n  ]\n}\n[/block]\n<div align=\"right\"><a href=\"#top\">top</a></div>\n\n###Filter by an entity's properties\n\nOnce you've selected an entity, you can filter by that entity's properties. Click **+ Add property** below each entity to add filters. Take advantage of the search box's partial matching functionality to generate a list of properties and values to help you get started.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/d389df6-Screen_Shot_2016-11-15_at_1.47.47_PM.png\",\n        \"Screen Shot 2016-11-15 at 1.47.47 PM.png\",\n        296,\n        448,\n        \"#db6565\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n<div align=\"right\"><a href=\"#top\">top</a></div>\n\n###View results in the table\n\nThe table below the Data Browser contains a list of UUIDs for the entities which match your query. This table allows you to review returned results, but it does not allow you to select or filter results. All selection and filtering have to be done via the query on the Data Browser canvas.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/0918bf0-Screen_Shot_2016-11-30_at_4.31.09_PM.png\",\n        \"Screen Shot 2016-11-30 at 4.31.09 PM.png\",\n        1410,\n        244,\n        \"#2f5666\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n<div align=\"right\"><a href=\"#top\">top</a></div>\n\n###Access data for use in your project\n\nOnce you've built a query, you can access the resulting data for use in a project. Learn more about [accessing data from the Data Browser](doc:access-data-from-the-data-browser).\n\n<div align=\"right\"<a href=\"#top\">top</a></div>\n\n##Example: build a query\n\n###Objective\n This query selects Cases that:\n  * are diagnosed with Lung Adenocarcinoma\n  * are males with donated samples of primary tumor tissue\n  * have been analyzed with RNA-Seq\n  * have FASTQ files produced by this experimental strategy\n\n<div align=\"right\"><a href=\"#top\">top</a></div>\n\n###Procedure\n1. Select the **Case** entity, as shown below.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/117201c-c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg\",\n        \"c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg\",\n        1974,\n        1326,\n        \"#3e756e\"\n      ]\n    }\n  ]\n}\n[/block]\n2.  Click **Has Diagnosis** and select **Has Disease Type** from the properties below **Case**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/bc80565-3b6f53a-Screen_Shot_2016-09-02_at_3.07.10_PM.jpeg\",\n        \"3b6f53a-Screen_Shot_2016-09-02_at_3.07.10_PM.jpeg\",\n        918,\n        648,\n        \"#406e75\"\n      ]\n    }\n  ]\n}\n[/block]\n3. Add a filter for the **Disease Type**. Use the **Text search bar** to look up and select **Lung Adenocarcinoma**. Then, click **Add property** to apply your selection. \n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/e587cac-eae53bd-Screen_Shot_2016-08-17_at_11.19.55_AM.jpeg\",\n        \"eae53bd-Screen_Shot_2016-08-17_at_11.19.55_AM.jpeg\",\n        934,\n        748,\n        \"#41757a\"\n      ]\n    }\n  ]\n}\n[/block]\n4. Select **Has Demographic** on the **Case** node, and click **Gender**.\n5. Select **Male** and click **Add property**.\n6. To filter for **Samples** with a **Sample Type** of primary tumor, click on **Sample** from the list of entities next to the **Case** node.\n7. Click **+Add property** and select **Sample type.**\n8. Look up and select **Primary Tumor**. Click **Add property** to add your selection.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/bcf1156-524574b-Screen_Shot_2016-08-17_at_11.21.50_AM.jpeg\",\n        \"524574b-Screen_Shot_2016-08-17_at_11.21.50_AM.jpeg\",\n        1696,\n        986,\n        \"#574da4\"\n      ]\n    }\n  ]\n}\n[/block]\n9. Next to **Sample**, select the **File** entity.\n10. On the **File** entity, click **+Add property** and choose **Experimental Strategy**. Search for and select **RNA - Seq**. Add the filter by clicking **Add property**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/4b494c9-e2e1250-Screen_Shot_2016-08-17_at_11.22.47_AM.jpeg\",\n        \"e2e1250-Screen_Shot_2016-08-17_at_11.22.47_AM.jpeg\",\n        2206,\n        1104,\n        \"#efeef0\"\n      ]\n    }\n  ]\n}\n[/block]\n11.Click on **+Add property** below the File entity once more to select **Data Format** with a filter of **TARGZ**. This filters for FASTQ files stored in the TARGZ format. Finish your selection by clicking **Add property**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/71d75db-dc5e725-Screen_Shot_2016-08-17_at_11.24.41_AM.jpeg\",\n        \"dc5e725-Screen_Shot_2016-08-17_at_11.24.41_AM.jpeg\",\n        2238,\n        1080,\n        \"#4775bd\"\n      ]\n    }\n  ]\n}\n[/block]\nNow that you have filtered for your desired data, you may import these files into your project for further analysis. Read more about [accessing data from the Data Browser](doc:access-data-from-the-data-browser).\n\nTo save this query, click **Save** from the **Queries** drop-down menu on the top of the canvas.\n\nThat's it! You've successfully built a query from scratch and found FASTQ files analyzed with RNA - Sequencing technology from primary tumor tissue donated by males with Lung Adenocarcinoma.\n\n<div align=\"right\"><a href=\"#top\">top</a></div>","excerpt":"<a href=\"query-datasets\" style=\"color:#132c56\">QUERY DATASETS</a> > <a href=\"about-the-data-browser\" style=\"color:#132c56\">About the Data Browser</a> > Data Browser query: start from scratch","slug":"data-browser-query-start-from-scratch","type":"basic","title":"↳ Data Browser query: start from scratch"}

↳ Data Browser query: start from scratch

<a href="query-datasets" style="color:#132c56">QUERY DATASETS</a> > <a href="about-the-data-browser" style="color:#132c56">About the Data Browser</a> > Data Browser query: start from scratch

[block:callout] { "type": "warning", "title": "On this page:", "body": "[Overview](#section-overview)\n[Anatomy of a query](#section-anatomy-of-a-query)\n[Start from an entity](#section-start-from-an-entity)\n[Filter by an entity's properties](#section-filter-by-an-entity-s-properties)\n[View results in the table](#section-view-results-in-the-table)\n[Access data for use in your project](#section-access-data-for-use-in-your-project)\n[Example: build a query](#section-example-build-a-query)\n[Objective](#section-objective)\n[Procedure](#section-procedure)" } [/block] ##Overview Build your own queries from scratch using the metadata associated with each dataset. Metadata consists of properties, which describe each dataset’s entities, and their values. Entities are particular resources with UUIDs, such as files, cases, samples, and cell lines. Learn more [about metadata for datasets](about-metadata-for-datasets). On this page, learn about the [parts of a query](#section-anatomy-of-a-query). Then, walk through an example demonstrating [building a query from scratch](#section-example-build-a-query). <div align="right"><a href="#top">top</a></div> ##Anatomy of a query ###Start from an entity The entities of each dataset are displayed on the Data Browser when you first open it, as shown below. Start your queries from a dataset's entities. Simply click on an entity, such as **Case** below, to start. [block:image] { "images": [ { "image": [ "https://files.readme.io/3ebb971-c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg", "c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg", 1974, 1326, "#3e756e" ] } ] } [/block] Add additional entities by clicking on a previously added entity. A list of entities associated with the first one appears, as shown below. For instance, a **Case** can have associated **Files** (about the case), **Samples** (taken from the patient), and **Drug therapies** (given to the patient). Hover over an entity for more information. [block:image] { "images": [ { "image": [ "https://files.readme.io/22b4a2d-HHcEiAHQZGeSZc1ra23l_Screen_Shot_2016-06-10_at_3.58.33_PM_2_copy_1.jpg", "HHcEiAHQZGeSZc1ra23l_Screen Shot 2016-06-10 at 3.58.33 PM (2) copy (1).jpg", 718, 445, "#426d75" ] } ] } [/block] <div align="right"><a href="#top">top</a></div> ###Filter by an entity's properties Once you've selected an entity, you can filter by that entity's properties. Click **+ Add property** below each entity to add filters. Take advantage of the search box's partial matching functionality to generate a list of properties and values to help you get started. [block:image] { "images": [ { "image": [ "https://files.readme.io/d389df6-Screen_Shot_2016-11-15_at_1.47.47_PM.png", "Screen Shot 2016-11-15 at 1.47.47 PM.png", 296, 448, "#db6565" ], "border": true } ] } [/block] <div align="right"><a href="#top">top</a></div> ###View results in the table The table below the Data Browser contains a list of UUIDs for the entities which match your query. This table allows you to review returned results, but it does not allow you to select or filter results. All selection and filtering have to be done via the query on the Data Browser canvas. [block:image] { "images": [ { "image": [ "https://files.readme.io/0918bf0-Screen_Shot_2016-11-30_at_4.31.09_PM.png", "Screen Shot 2016-11-30 at 4.31.09 PM.png", 1410, 244, "#2f5666" ], "border": true } ] } [/block] <div align="right"><a href="#top">top</a></div> ###Access data for use in your project Once you've built a query, you can access the resulting data for use in a project. Learn more about [accessing data from the Data Browser](doc:access-data-from-the-data-browser). <div align="right"<a href="#top">top</a></div> ##Example: build a query ###Objective This query selects Cases that: * are diagnosed with Lung Adenocarcinoma * are males with donated samples of primary tumor tissue * have been analyzed with RNA-Seq * have FASTQ files produced by this experimental strategy <div align="right"><a href="#top">top</a></div> ###Procedure 1. Select the **Case** entity, as shown below. [block:image] { "images": [ { "image": [ "https://files.readme.io/117201c-c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg", "c7a0f0a-Screen_Shot_2016-08-17_at_11.17.49_AM.jpeg", 1974, 1326, "#3e756e" ] } ] } [/block] 2. Click **Has Diagnosis** and select **Has Disease Type** from the properties below **Case**. [block:image] { "images": [ { "image": [ "https://files.readme.io/bc80565-3b6f53a-Screen_Shot_2016-09-02_at_3.07.10_PM.jpeg", "3b6f53a-Screen_Shot_2016-09-02_at_3.07.10_PM.jpeg", 918, 648, "#406e75" ] } ] } [/block] 3. Add a filter for the **Disease Type**. Use the **Text search bar** to look up and select **Lung Adenocarcinoma**. Then, click **Add property** to apply your selection. [block:image] { "images": [ { "image": [ "https://files.readme.io/e587cac-eae53bd-Screen_Shot_2016-08-17_at_11.19.55_AM.jpeg", "eae53bd-Screen_Shot_2016-08-17_at_11.19.55_AM.jpeg", 934, 748, "#41757a" ] } ] } [/block] 4. Select **Has Demographic** on the **Case** node, and click **Gender**. 5. Select **Male** and click **Add property**. 6. To filter for **Samples** with a **Sample Type** of primary tumor, click on **Sample** from the list of entities next to the **Case** node. 7. Click **+Add property** and select **Sample type.** 8. Look up and select **Primary Tumor**. Click **Add property** to add your selection. [block:image] { "images": [ { "image": [ "https://files.readme.io/bcf1156-524574b-Screen_Shot_2016-08-17_at_11.21.50_AM.jpeg", "524574b-Screen_Shot_2016-08-17_at_11.21.50_AM.jpeg", 1696, 986, "#574da4" ] } ] } [/block] 9. Next to **Sample**, select the **File** entity. 10. On the **File** entity, click **+Add property** and choose **Experimental Strategy**. Search for and select **RNA - Seq**. Add the filter by clicking **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/4b494c9-e2e1250-Screen_Shot_2016-08-17_at_11.22.47_AM.jpeg", "e2e1250-Screen_Shot_2016-08-17_at_11.22.47_AM.jpeg", 2206, 1104, "#efeef0" ] } ] } [/block] 11.Click on **+Add property** below the File entity once more to select **Data Format** with a filter of **TARGZ**. This filters for FASTQ files stored in the TARGZ format. Finish your selection by clicking **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/71d75db-dc5e725-Screen_Shot_2016-08-17_at_11.24.41_AM.jpeg", "dc5e725-Screen_Shot_2016-08-17_at_11.24.41_AM.jpeg", 2238, 1080, "#4775bd" ] } ] } [/block] Now that you have filtered for your desired data, you may import these files into your project for further analysis. Read more about [accessing data from the Data Browser](doc:access-data-from-the-data-browser). To save this query, click **Save** from the **Queries** drop-down menu on the top of the canvas. That's it! You've successfully built a query from scratch and found FASTQ files analyzed with RNA - Sequencing technology from primary tumor tissue donated by males with Lung Adenocarcinoma. <div align="right"><a href="#top">top</a></div>