{"_id":"564a046ee2efd717002afd11","category":{"_id":"56fbb83d8f21c817002af880","version":"55faf11ba62ba1170021a9aa","__v":0,"project":"55faf11ba62ba1170021a9a7","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-03-30T11:27:57.862Z","from_sync":false,"order":1,"slug":"tutorials","title":"TUTORIALS"},"parentDoc":null,"project":"55faf11ba62ba1170021a9a7","__v":214,"version":{"_id":"55faf11ba62ba1170021a9aa","project":"55faf11ba62ba1170021a9a7","__v":37,"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"],"is_deprecated":false,"is_hidden":false,"is_beta":true,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"user":"554290cd6592e60d00027d17","updates":[],"next":{"pages":[],"description":""},"createdAt":"2015-11-16T16:29:34.924Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"settings":"","results":{"codes":[]},"auth":"required","params":[],"url":""},"isReference":false,"order":1,"body":"##Prerequisites\n\nIn order to be able to use **all** resources which are discussed in this QuickStart you need to have access to [TCGA Controlled Data](tcga-data-access#controlled-data) through dbGap. if you don’t have access to TCGA Controlled Data, you can still follow the QuickStart, but without the possibility to add Controlled Data to your project.\n\nHowever, you can still analyze the [Open Data from TCGA dataset](tcga-data-access#open-data) using the available apps without special permission from dbGaP.\n\n##Procedure\n\nWe'll start by creating a project and populating it with TCGA files. Then we'll use one of the CGC RNA-Seq workflows, RNA-Seq Alignment - STAR, to carry out the analysis. Finally, we'll examine our results.\n[block:callout]\n{\n  \"type\": \"warning\",\n  \"title\": \"On this page:\",\n  \"body\": \"* [Create a project](#section--create-a-project-)\\n* [Add analysis data](#section-add-analysis-data)\\n* [Find files associated with the case](#section-find-files-associated-with-the-case)\\n* [Add the TCGA file to your project](#section-add-the-tcga-file-to-your-project)\\n* [Choose a public workflow](#section-choose-a-public-workflow)\\n* [Run the analysis](#section-run-the-analysis)\\n* [View the results](#section-view-the-results)\"\n}\n[/block]\n##**Create a project **\n \nThe first step to running an analysis on the CGC is to create a project.\n1. **To create a project:**\n    a. Choose **Create a project **under **Projects** in the top navigation bar and the window for naming your project will be shown.\n    b. Enter **Quickstart** as the project name.\n    c. Choose **Pilot Funds** as the billing group.\n    d. Select **This project will contain TCGA Controlled Data** since we’ll be using TCGA Controlled Data.\n    e. Click **Create**.\n\nThis concludes the procedure for creating a new project. The next step is adding analysis data.\n\n##Add analysis data\n\nIn this Quickstart, we will use the TCGA data that is hosted on the CGC to analyze Glioblastoma patient with TP53 missense mutation.\n\n2. **To add analysis data**:\n a. The first step is selecting all cases that belong to the Glioblastoma disease (GBM). Choose **Data Overview** from the **Data** menu.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/6c4d048-choose-data-overview.jpg\",\n        \"choose-data-overview.jpg\",\n        709,\n        389,\n        \"#e7e9ec\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n\nThe Data Overview page will be displayed, as shown below.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/245ca9c-data-overview-inc-case-exp2.jpg\",\n        \"data-overview-inc-case-exp2.jpg\",\n        1158,\n        963,\n        \"#e4e6e7\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nb. Select **GBM** from the **Cases by Disease** section.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/bc3c5dc-disease-section_3.jpg\",\n        \"disease-section_3.jpg\",\n        1119,\n        256,\n        \"#dfe5ee\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nThe Disease Details section below will show:\n  * The total number of cases.\n  * The female/male distribution.\n  * Ethnicity.\n  * Age at diagnosis.\n  * The sample type.\n \nHover the bars to see the number of available cases for each of the categories. The next step is to filter these cases using the Case Explorer.\n[block:callout]\n{\n  \"type\": \"info\",\n  \"body\": \"The [Case Explorer](doc:the-case-explorer) is designed to allow researchers to easily find a subset of TCGA data based on a disease and gene mutation.\"\n}\n[/block]\nc. Click **Case Explorer** in the upper right corner (see above) to open the Case Explorer.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/2706441-choosing-a-case_4.jpg\",\n        \"choosing-a-case_4.jpg\",\n        2616,\n        1510,\n        \"#e9ebeb\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nd.Click **TP53** in the **Top mutated genes in GBM** table in the upper right corner, as shown above. All available cases will be displayed on the scatter plot.\n[block:callout]\n{\n  \"type\": \"info\",\n  \"body\": \"The scatter plot is populated to show the relation between copy number variation (CNV) on the **y-axis** and gene expression levels on the **x-axis** for the selected gene in patients with GBM. \\n\\nThe colors of the circles represent different types of mutation (see the **Variant Classification** filter below the scatter plot).\",\n  \"title\": \"Circle colors on the scatter plot\"\n}\n[/block]\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/aabb734-choose-a-case-ff_5.jpg\",\n        \"choose-a-case-ff_5.jpg\",\n        1952,\n        1082,\n        \"#1a4c81\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\ne. Select a case, as shown above. The case information will be displayed in the bottom of the page.\nf. Click **Continue to Data Browser** to copy the file for the case we selected. This will take us to the Data Browser where we can find the RNA-Seq raw sequencing reads from this case.\n[block:callout]\n{\n  \"type\": \"info\",\n  \"body\": \"Copy multiple files at once by selecting them all before clicking the **Continue to Data Browser** button.\",\n  \"title\": \"Selecting multiple Cases\"\n}\n[/block]\n\n### Find files associated with the case\n\nUsing the Data Browser, we'll build a query to filter data from this case by combining metadata attributes. In the example below, we will choose RNA-Seq as experimental strategy and TARGZ as data format, since RNA-Seq raw sequencing reads in TCGA data are compressed in TARGZ format. Upon opening it, the Data Browser will display the case we picked using the Case Explorer.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/3f06999-data-browser-case-filter_6.jpg\",\n        \"data-browser-case-filter_6.jpg\",\n        682,\n        693,\n        \"#e8d9d9\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n3. **To find RNA-Seq files associated with this case:**\n     a. Choose the RNA-seq as experimental strategy:\n     &nbsp;&nbsp;&nbsp;&nbsp;  i. Click **File**.\n     &nbsp; &nbsp; ii. Click **Add property**.\n     &nbsp;&nbsp; iii. Select **Experimental strategy**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/22bda40-exp-strat-i-ii-iii-ff.jpg\",\n        \"exp-strat-i-ii-iii-ff.jpg\",\n        705,\n        470,\n        \"#2c589e\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iv. Next, choose the **RNA-Seq** metadata filter.\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;v. Click **Add property**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/e4f36e5-rna-seq-iv-v8.jpg\",\n        \"rna-seq-iv-v8.jpg\",\n        734,\n        493,\n        \"#28589f\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;b. Repeat this procedure to add **TARGZ data format **as a property.\n  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; i. Click **Add property**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/c979c2a-add-property-i9.jpg\",\n        \"add-property-i9.jpg\",\n        693,\n        292,\n        \"#ae5792\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ii. Click **Data format**.\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iii. Choose **TARGZ filter**.\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iv. Click **Add property**.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/94aff73-targz-ii-iii-iv10.jpg\",\n        \"targz-ii-iii-iv10.jpg\",\n        685,\n        497,\n        \"#f4f3f1\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nThis will give you all the files created as a result of the RNA-Seq experiment.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/bb6ca18-1case-1file11.jpg\",\n        \"1case-1file11.jpg\",\n        1115,\n        859,\n        \"#f0edeb\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nClick the refresh icon next to the count cards below the Data Browser to display the number of cases and results returned by the query, which is one case and one file. The next step is adding the TCGA file to your project.\n\n###Add the TCGA file to your project\n\n4. **To add the TCGA file to your project after finding it using the Data Browser**:\n     a. Click **Copy files to project** in the upper right corner.\n     b. Choose your **Quickstart** project.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/c87c113-cgc_quickstart_final.png\",\n        \"cgc_quickstart_final.png\",\n        1287,\n        692,\n        \"#e5e8eb\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nThe confirmation window will be shown.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/c636f61-copy-selected-files-modal_14.jpg\",\n        \"copy-selected-files-modal_14.jpg\",\n        440,\n        325,\n        \"#e8eee8\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;c. Click **Copy selected files**.\n\nThis concludes the procedure of adding the TCGA file to your project. The next step is choosing the workflow for your analysis.\n\n##Choose a public workflow\n\nWith the analysis data now prepared, we need to choose a workflow for performing the analysis. We'll use the public workflow **RNA-seq Alignment - STAR for TCGA PE tar**, which uses the popular split-read aligner, STAR, to map reads to a reference genome.\n\nThis workflow utilizes a transcript annotation file (GTF) to speed read mapping across known splice junctions. It will generate alignment files that can then be compared for differential expression, analyzed to discover novel transcripts, or viewed directly in the genome browser.\n\n**5. To select a public workflow**:\n   &nbsp;&nbsp;&nbsp;&nbsp; a. Click **Public Apps** in the top bar navigation.\n   &nbsp;&nbsp;&nbsp;&nbsp;  b. Search for the **RNA-seq Alignment - STAR for TCGA PE tar**.\n   &nbsp;&nbsp;&nbsp;&nbsp; c. Click **Copy** below the workflow.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/c1d69d6-choose-pub-app-abc15.jpg\",\n        \"choose-pub-app-abc15.jpg\",\n        929,\n        792,\n        \"#f4f4f6\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nThe window for selecting the target project will be displayed.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/b381bfd-select-public-workflow_16.jpg\",\n        \"select-public-workflow_16.jpg\",\n        438,\n        304,\n        \"#eaeaea\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; d. Choose your **Quickstart** project.\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; e. Click **Copy**.\n    \nThis will copy the workflow to your project apps. The next step is running the analysis.\n\n##Run the analysis\n\nNow that the analysis data and the workflow are ready, it's time to run the analysis.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/e1ef94d-run-wf-203_17.jpg\",\n        \"run-wf-203_17.jpg\",\n        1125,\n        441,\n        \"#18538d\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n**6. To run the analysis**:\n   &nbsp;&nbsp;&nbsp;&nbsp; a. Click the **Apps** tab in your Quickstart project.\n   &nbsp;&nbsp;&nbsp;&nbsp; b. Click the run icon next to the **RNA-seq Alignment - STAR for TCGA PE** tar workflow.\n\nThis will open the draft task page and a pop-up window which contains the suggested reference files for this workflow.\n[block:callout]\n{\n  \"type\": \"info\",\n  \"body\": \"For all public workflows on the CGC our team of bioinformaticians has chosen a set of recommended input files. This allows you to quickly add all required reference files.\"\n}\n[/block]\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/5548fb1-suggested-files_18.jpg\",\n        \"suggested-files_18.jpg\",\n        1066,\n        597,\n        \"#807a80\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n&nbsp;&nbsp;&nbsp;&nbsp; c. Click **Copy** and the suggested files will be copied to your project and added as input files to your workflow.\n&nbsp;&nbsp;&nbsp;&nbsp; d. Next, click **Pick file(s)** under **Input Read Files** to locate the analysis data that we have previously added to the project using the Data Browser and Case Explorer.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/3fc7675-pick-inputread-files_208_19.jpg\",\n        \"pick-inputread-files_208_19.jpg\",\n        1079,\n        707,\n        \"#1c548f\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\nThe file picker will be shown.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/a53a884-adding-analysis-data-using-file-browser20.jpg\",\n        \"adding-analysis-data-using-file-browser20.jpg\",\n        921,\n        413,\n        \"#eceef0\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\ne. Select **TCGAG17498.TCGA-02-2483-01A-01R-1849-01.2.tar.gz**\nf.  Click **Select** and the analysis data will be added to the workflow. \n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/8177ee2-added-analysis-data_209_21.jpg\",\n        \"added-analysis-data_209_21.jpg\",\n        1082,\n        675,\n        \"#1d548e\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n Now that all the required input files for the workflow are set, click **Run** to start the analysis.\n \nWhen you start the task, a new page opens displaying the task's properties. The status will be a progress bar (if the task is still running) or a label detailing whether the task has completed, been aborted or failed.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/dea59ba-task-status-206_22.jpg\",\n        \"task-status-206_22.jpg\",\n        1170,\n        666,\n        \"#ebecee\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n Additional information, including how to check the status of the task or how to troubleshoot in case of the failed task, is available in the documentation on [task statistics](doc:view-task-stats).\n\n## View the results\n\n7. **To see the results of your task**:\n    a. Open the task page.\n    b. Click on any of the files in the Outputs column (e.g. output_bam to review the alignment using the Genome Browser).\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/5679552-cgc_quickstart_final.png\",\n        \"cgc_quickstart_final.png\",\n        1287,\n        692,\n        \"#e5e8eb\"\n      ],\n      \"border\": true\n    }\n  ]\n}\n[/block]\n##Quickstart video\n[block:embed]\n{\n  \"html\": false,\n  \"url\": \"https://drive.google.com/a/sbgenomics.com/file/d/0B4n0VAdh2ImHZ1B5ZU5jUFFOSUk/preview\",\n  \"title\": \"QuickStart\",\n  \"favicon\": \"https://ssl.gstatic.com/docs/doclist/images/icon_14_video_favicon.ico\",\n  \"image\": \"https://lh3.googleusercontent.com/4MZr_rbh-YiD-tfKgJQgKIq4UySTM0d5KsDo5j4WJ77AtRqdJRpdBA=w1200-h630-p\",\n  \"iframe\": true,\n  \"width\": \"100%\",\n  \"height\": \"420\"\n}\n[/block]\n<div align=\"right\"><a href=\"#section-prerequisites\">top</a></div>","excerpt":"To introduce you to the major features of the CGC, this QuickStart will walk through a simple RNA sequencing analysis.\n\n[Watch and learn from the video guide](http://docs.cancergenomicscloud.org/docs/quickstart#section-quickstart-video)","slug":"quickstart","type":"basic","title":"QuickStart"}

QuickStart

To introduce you to the major features of the CGC, this QuickStart will walk through a simple RNA sequencing analysis. [Watch and learn from the video guide](http://docs.cancergenomicscloud.org/docs/quickstart#section-quickstart-video)

##Prerequisites In order to be able to use **all** resources which are discussed in this QuickStart you need to have access to [TCGA Controlled Data](tcga-data-access#controlled-data) through dbGap. if you don’t have access to TCGA Controlled Data, you can still follow the QuickStart, but without the possibility to add Controlled Data to your project. However, you can still analyze the [Open Data from TCGA dataset](tcga-data-access#open-data) using the available apps without special permission from dbGaP. ##Procedure We'll start by creating a project and populating it with TCGA files. Then we'll use one of the CGC RNA-Seq workflows, RNA-Seq Alignment - STAR, to carry out the analysis. Finally, we'll examine our results. [block:callout] { "type": "warning", "title": "On this page:", "body": "* [Create a project](#section--create-a-project-)\n* [Add analysis data](#section-add-analysis-data)\n* [Find files associated with the case](#section-find-files-associated-with-the-case)\n* [Add the TCGA file to your project](#section-add-the-tcga-file-to-your-project)\n* [Choose a public workflow](#section-choose-a-public-workflow)\n* [Run the analysis](#section-run-the-analysis)\n* [View the results](#section-view-the-results)" } [/block] ##**Create a project ** The first step to running an analysis on the CGC is to create a project. 1. **To create a project:** a. Choose **Create a project **under **Projects** in the top navigation bar and the window for naming your project will be shown. b. Enter **Quickstart** as the project name. c. Choose **Pilot Funds** as the billing group. d. Select **This project will contain TCGA Controlled Data** since we’ll be using TCGA Controlled Data. e. Click **Create**. This concludes the procedure for creating a new project. The next step is adding analysis data. ##Add analysis data In this Quickstart, we will use the TCGA data that is hosted on the CGC to analyze Glioblastoma patient with TP53 missense mutation. 2. **To add analysis data**: a. The first step is selecting all cases that belong to the Glioblastoma disease (GBM). Choose **Data Overview** from the **Data** menu. [block:image] { "images": [ { "image": [ "https://files.readme.io/6c4d048-choose-data-overview.jpg", "choose-data-overview.jpg", 709, 389, "#e7e9ec" ], "border": true } ] } [/block] The Data Overview page will be displayed, as shown below. [block:image] { "images": [ { "image": [ "https://files.readme.io/245ca9c-data-overview-inc-case-exp2.jpg", "data-overview-inc-case-exp2.jpg", 1158, 963, "#e4e6e7" ], "border": true } ] } [/block] b. Select **GBM** from the **Cases by Disease** section. [block:image] { "images": [ { "image": [ "https://files.readme.io/bc3c5dc-disease-section_3.jpg", "disease-section_3.jpg", 1119, 256, "#dfe5ee" ], "border": true } ] } [/block] The Disease Details section below will show: * The total number of cases. * The female/male distribution. * Ethnicity. * Age at diagnosis. * The sample type. Hover the bars to see the number of available cases for each of the categories. The next step is to filter these cases using the Case Explorer. [block:callout] { "type": "info", "body": "The [Case Explorer](doc:the-case-explorer) is designed to allow researchers to easily find a subset of TCGA data based on a disease and gene mutation." } [/block] c. Click **Case Explorer** in the upper right corner (see above) to open the Case Explorer. [block:image] { "images": [ { "image": [ "https://files.readme.io/2706441-choosing-a-case_4.jpg", "choosing-a-case_4.jpg", 2616, 1510, "#e9ebeb" ], "border": true } ] } [/block] d.Click **TP53** in the **Top mutated genes in GBM** table in the upper right corner, as shown above. All available cases will be displayed on the scatter plot. [block:callout] { "type": "info", "body": "The scatter plot is populated to show the relation between copy number variation (CNV) on the **y-axis** and gene expression levels on the **x-axis** for the selected gene in patients with GBM. \n\nThe colors of the circles represent different types of mutation (see the **Variant Classification** filter below the scatter plot).", "title": "Circle colors on the scatter plot" } [/block] [block:image] { "images": [ { "image": [ "https://files.readme.io/aabb734-choose-a-case-ff_5.jpg", "choose-a-case-ff_5.jpg", 1952, 1082, "#1a4c81" ], "border": true } ] } [/block] e. Select a case, as shown above. The case information will be displayed in the bottom of the page. f. Click **Continue to Data Browser** to copy the file for the case we selected. This will take us to the Data Browser where we can find the RNA-Seq raw sequencing reads from this case. [block:callout] { "type": "info", "body": "Copy multiple files at once by selecting them all before clicking the **Continue to Data Browser** button.", "title": "Selecting multiple Cases" } [/block] ### Find files associated with the case Using the Data Browser, we'll build a query to filter data from this case by combining metadata attributes. In the example below, we will choose RNA-Seq as experimental strategy and TARGZ as data format, since RNA-Seq raw sequencing reads in TCGA data are compressed in TARGZ format. Upon opening it, the Data Browser will display the case we picked using the Case Explorer. [block:image] { "images": [ { "image": [ "https://files.readme.io/3f06999-data-browser-case-filter_6.jpg", "data-browser-case-filter_6.jpg", 682, 693, "#e8d9d9" ], "border": true } ] } [/block] 3. **To find RNA-Seq files associated with this case:** a. Choose the RNA-seq as experimental strategy: &nbsp;&nbsp;&nbsp;&nbsp; i. Click **File**. &nbsp; &nbsp; ii. Click **Add property**. &nbsp;&nbsp; iii. Select **Experimental strategy**. [block:image] { "images": [ { "image": [ "https://files.readme.io/22bda40-exp-strat-i-ii-iii-ff.jpg", "exp-strat-i-ii-iii-ff.jpg", 705, 470, "#2c589e" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iv. Next, choose the **RNA-Seq** metadata filter. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;v. Click **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/e4f36e5-rna-seq-iv-v8.jpg", "rna-seq-iv-v8.jpg", 734, 493, "#28589f" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;b. Repeat this procedure to add **TARGZ data format **as a property. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; i. Click **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/c979c2a-add-property-i9.jpg", "add-property-i9.jpg", 693, 292, "#ae5792" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ii. Click **Data format**. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iii. Choose **TARGZ filter**. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;iv. Click **Add property**. [block:image] { "images": [ { "image": [ "https://files.readme.io/94aff73-targz-ii-iii-iv10.jpg", "targz-ii-iii-iv10.jpg", 685, 497, "#f4f3f1" ], "border": true } ] } [/block] This will give you all the files created as a result of the RNA-Seq experiment. [block:image] { "images": [ { "image": [ "https://files.readme.io/bb6ca18-1case-1file11.jpg", "1case-1file11.jpg", 1115, 859, "#f0edeb" ], "border": true } ] } [/block] Click the refresh icon next to the count cards below the Data Browser to display the number of cases and results returned by the query, which is one case and one file. The next step is adding the TCGA file to your project. ###Add the TCGA file to your project 4. **To add the TCGA file to your project after finding it using the Data Browser**: a. Click **Copy files to project** in the upper right corner. b. Choose your **Quickstart** project. [block:image] { "images": [ { "image": [ "https://files.readme.io/c87c113-cgc_quickstart_final.png", "cgc_quickstart_final.png", 1287, 692, "#e5e8eb" ], "border": true } ] } [/block] The confirmation window will be shown. [block:image] { "images": [ { "image": [ "https://files.readme.io/c636f61-copy-selected-files-modal_14.jpg", "copy-selected-files-modal_14.jpg", 440, 325, "#e8eee8" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;c. Click **Copy selected files**. This concludes the procedure of adding the TCGA file to your project. The next step is choosing the workflow for your analysis. ##Choose a public workflow With the analysis data now prepared, we need to choose a workflow for performing the analysis. We'll use the public workflow **RNA-seq Alignment - STAR for TCGA PE tar**, which uses the popular split-read aligner, STAR, to map reads to a reference genome. This workflow utilizes a transcript annotation file (GTF) to speed read mapping across known splice junctions. It will generate alignment files that can then be compared for differential expression, analyzed to discover novel transcripts, or viewed directly in the genome browser. **5. To select a public workflow**: &nbsp;&nbsp;&nbsp;&nbsp; a. Click **Public Apps** in the top bar navigation. &nbsp;&nbsp;&nbsp;&nbsp; b. Search for the **RNA-seq Alignment - STAR for TCGA PE tar**. &nbsp;&nbsp;&nbsp;&nbsp; c. Click **Copy** below the workflow. [block:image] { "images": [ { "image": [ "https://files.readme.io/c1d69d6-choose-pub-app-abc15.jpg", "choose-pub-app-abc15.jpg", 929, 792, "#f4f4f6" ], "border": true } ] } [/block] The window for selecting the target project will be displayed. [block:image] { "images": [ { "image": [ "https://files.readme.io/b381bfd-select-public-workflow_16.jpg", "select-public-workflow_16.jpg", 438, 304, "#eaeaea" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; d. Choose your **Quickstart** project. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; e. Click **Copy**. This will copy the workflow to your project apps. The next step is running the analysis. ##Run the analysis Now that the analysis data and the workflow are ready, it's time to run the analysis. [block:image] { "images": [ { "image": [ "https://files.readme.io/e1ef94d-run-wf-203_17.jpg", "run-wf-203_17.jpg", 1125, 441, "#18538d" ], "border": true } ] } [/block] **6. To run the analysis**: &nbsp;&nbsp;&nbsp;&nbsp; a. Click the **Apps** tab in your Quickstart project. &nbsp;&nbsp;&nbsp;&nbsp; b. Click the run icon next to the **RNA-seq Alignment - STAR for TCGA PE** tar workflow. This will open the draft task page and a pop-up window which contains the suggested reference files for this workflow. [block:callout] { "type": "info", "body": "For all public workflows on the CGC our team of bioinformaticians has chosen a set of recommended input files. This allows you to quickly add all required reference files." } [/block] [block:image] { "images": [ { "image": [ "https://files.readme.io/5548fb1-suggested-files_18.jpg", "suggested-files_18.jpg", 1066, 597, "#807a80" ], "border": true } ] } [/block] &nbsp;&nbsp;&nbsp;&nbsp; c. Click **Copy** and the suggested files will be copied to your project and added as input files to your workflow. &nbsp;&nbsp;&nbsp;&nbsp; d. Next, click **Pick file(s)** under **Input Read Files** to locate the analysis data that we have previously added to the project using the Data Browser and Case Explorer. [block:image] { "images": [ { "image": [ "https://files.readme.io/3fc7675-pick-inputread-files_208_19.jpg", "pick-inputread-files_208_19.jpg", 1079, 707, "#1c548f" ], "border": true } ] } [/block] The file picker will be shown. [block:image] { "images": [ { "image": [ "https://files.readme.io/a53a884-adding-analysis-data-using-file-browser20.jpg", "adding-analysis-data-using-file-browser20.jpg", 921, 413, "#eceef0" ], "border": true } ] } [/block] e. Select **TCGAG17498.TCGA-02-2483-01A-01R-1849-01.2.tar.gz** f. Click **Select** and the analysis data will be added to the workflow. [block:image] { "images": [ { "image": [ "https://files.readme.io/8177ee2-added-analysis-data_209_21.jpg", "added-analysis-data_209_21.jpg", 1082, 675, "#1d548e" ], "border": true } ] } [/block] Now that all the required input files for the workflow are set, click **Run** to start the analysis. When you start the task, a new page opens displaying the task's properties. The status will be a progress bar (if the task is still running) or a label detailing whether the task has completed, been aborted or failed. [block:image] { "images": [ { "image": [ "https://files.readme.io/dea59ba-task-status-206_22.jpg", "task-status-206_22.jpg", 1170, 666, "#ebecee" ], "border": true } ] } [/block] Additional information, including how to check the status of the task or how to troubleshoot in case of the failed task, is available in the documentation on [task statistics](doc:view-task-stats). ## View the results 7. **To see the results of your task**: a. Open the task page. b. Click on any of the files in the Outputs column (e.g. output_bam to review the alignment using the Genome Browser). [block:image] { "images": [ { "image": [ "https://files.readme.io/5679552-cgc_quickstart_final.png", "cgc_quickstart_final.png", 1287, 692, "#e5e8eb" ], "border": true } ] } [/block] ##Quickstart video [block:embed] { "html": false, "url": "https://drive.google.com/a/sbgenomics.com/file/d/0B4n0VAdh2ImHZ1B5ZU5jUFFOSUk/preview", "title": "QuickStart", "favicon": "https://ssl.gstatic.com/docs/doclist/images/icon_14_video_favicon.ico", "image": "https://lh3.googleusercontent.com/4MZr_rbh-YiD-tfKgJQgKIq4UySTM0d5KsDo5j4WJ77AtRqdJRpdBA=w1200-h630-p", "iframe": true, "width": "100%", "height": "420" } [/block] <div align="right"><a href="#section-prerequisites">top</a></div>