{"_id":"584593e448293d1900d1fc0c","user":"5613e4f8fdd08f2b00437620","__v":1,"githubsync":"","version":{"_id":"55faf11ba62ba1170021a9aa","project":"55faf11ba62ba1170021a9a7","__v":40,"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","58ef66d88646742f009a0216","58f5d52d7891630f00fe4e77","59a555bccdbd85001bfb1442","5a2a81f688574d001e9934f5","5b080c8d7833b20003ddbb6f"],"is_deprecated":false,"is_hidden":false,"is_beta":true,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"category":{"_id":"58458b4fba4f1c0f009692bb","project":"55faf11ba62ba1170021a9a7","version":"55faf11ba62ba1170021a9aa","__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"},"project":"55faf11ba62ba1170021a9a7","parentDoc":null,"updates":["5b132b0bbc90f5000319ee16"],"next":{"pages":[],"description":""},"createdAt":"2016-12-05T16:20:52.483Z","link_external":false,"link_url":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":34,"body":"[block:callout]\n{\n  \"type\": \"warning\",\n  \"title\": \"On this page:\",\n  \"body\": \"* [Overview](#section-overview)\\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.\n\nEntities are particular resources with UUIDs, such as files, cases, samples, and cell lines. Learn more [about metadata for datasets](about-metadata-for-datasets).\n\nLearn about the [parts of a query](doc:data-browser-query-structure). Then, walk through an example demonstrating building a query from scratch below.\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##Procedure\n\n1. Choose **Data Browser** from the **Data** menu. \n2. Select a dataset.\n3. Select the **Case** entity, as shown below.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/8537308-choose-case-below.png\",\n        \"choose-case-below.png\",\n        915,\n        392,\n        \"#be5d49\"\n      ]\n    }\n  ]\n}\n[/block]\n4. Click **Investigation** and select the **Disease type** property.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/50e3a46-lung-adenocarcinoma.jpg\",\n        \"lung-adenocarcinoma.jpg\",\n        543,\n        282,\n        \"#5d5e5f\"\n      ]\n    }\n  ]\n}\n[/block]\n5. Search for \"Lung Adenocarcinoma\" select it, and click **Add property** to apply your selection. \n6. Next, click the **Case** entity again and then select the **Demographic** entity.\n7. Choose the **Gender** property, select **male** and click **Add property**. \n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/3c44287-add-demographic-male.jpg\",\n        \"add-demographic-male.jpg\",\n        518,\n        388,\n        \"#ebebea\"\n      ]\n    }\n  ]\n}\n[/block]\n8. To filter for **Samples** with a **Sample Type** of primary tumor, click the **Case** entity again and then click **Sample**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/1d94eec-add-primary-tumor.jpg\",\n        \"add-primary-tumor.jpg\",\n        510,\n        478,\n        \"#995e6b\"\n      ]\n    }\n  ]\n}\n[/block]\n9. Search for \"Primary tumor\" and click on it. \n10. Next, click the **Sample** entity and choose **File**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/c7eff36-add-rna-seq-exp-strategy.jpg\",\n        \"add-rna-seq-exp-strategy.jpg\",\n        514,\n        334,\n        \"#ededee\"\n      ]\n    }\n  ]\n}\n[/block]\n11. Search for the **Experimental strategy** property and select it.\n12. Then, select **RNA-Seq** and click **Add property**.\n\nNow that you have filtered for your desired data, by clicking **Copy files to project** 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[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/7116653-query-from-scratch.jpg\",\n        \"query-from-scratch.jpg\",\n        1211,\n        607,\n        \"#975c81\"\n      ]\n    }\n  ]\n}\n[/block]\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.","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* [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). Learn about the [parts of a query](doc:data-browser-query-structure). Then, walk through an example demonstrating building a query from scratch below. ##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 ##Procedure 1. Choose **Data Browser** from the **Data** menu. 2. Select a dataset. 3. Select the **Case** entity, as shown below. [block:image] { "images": [ { "image": [ "https://files.readme.io/8537308-choose-case-below.png", "choose-case-below.png", 915, 392, "#be5d49" ] } ] } [/block] 4. Click **Investigation** and select the **Disease type** property. [block:image] { "images": [ { "image": [ "https://files.readme.io/50e3a46-lung-adenocarcinoma.jpg", "lung-adenocarcinoma.jpg", 543, 282, "#5d5e5f" ] } ] } [/block] 5. Search for "Lung Adenocarcinoma" select it, and click **Add property** to apply your selection. 6. Next, click the **Case** entity again and then select the **Demographic** entity. 7. Choose the **Gender** property, select **male** and click **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/3c44287-add-demographic-male.jpg", "add-demographic-male.jpg", 518, 388, "#ebebea" ] } ] } [/block] 8. To filter for **Samples** with a **Sample Type** of primary tumor, click the **Case** entity again and then click **Sample**. [block:image] { "images": [ { "image": [ "https://files.readme.io/1d94eec-add-primary-tumor.jpg", "add-primary-tumor.jpg", 510, 478, "#995e6b" ] } ] } [/block] 9. Search for "Primary tumor" and click on it. 10. Next, click the **Sample** entity and choose **File**. [block:image] { "images": [ { "image": [ "https://files.readme.io/c7eff36-add-rna-seq-exp-strategy.jpg", "add-rna-seq-exp-strategy.jpg", 514, 334, "#ededee" ] } ] } [/block] 11. Search for the **Experimental strategy** property and select it. 12. Then, select **RNA-Seq** and click **Add property**. Now that you have filtered for your desired data, by clicking **Copy files to project** 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). [block:image] { "images": [ { "image": [ "https://files.readme.io/7116653-query-from-scratch.jpg", "query-from-scratch.jpg", 1211, 607, "#975c81" ] } ] } [/block] 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.