{"_id":"58f5d5cf914540250034e4bf","project":"55faf11ba62ba1170021a9a7","parentDoc":null,"user":"5767bc73bb15f40e00a28777","version":{"_id":"55faf11ba62ba1170021a9aa","project":"55faf11ba62ba1170021a9a7","__v":45,"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","5c222bed4bc358002f21459a","5c22412594a2a5005cc9e919","5c41ae1c33592700190a291e","5c8a525e2ba7b2003f9b153c","5cbf14d58c79c700ef2b502e"],"is_deprecated":false,"is_hidden":false,"is_beta":true,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"__v":0,"category":{"_id":"58f5d52d7891630f00fe4e77","project":"55faf11ba62ba1170021a9a7","version":"55faf11ba62ba1170021a9aa","__v":0,"sync":{"url":"","isSync":false},"reference":false,"createdAt":"2017-04-18T08:58:21.978Z","from_sync":false,"order":39,"slug":"data-cruncher","title":"DATA CRUNCHER"},"githubsync":"","metadata":{"title":"","description":"","image":[]},"updates":[],"next":{"pages":[],"description":""},"createdAt":"2017-04-18T09:01:03.544Z","link_external":false,"link_url":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":9,"body":"The files available in any Data Cruncher analysis belong to one of the following two types:\n* **Analysis files** - Files produced during the analysis or added to the analysis. These files appear under the **Files** tab in the analysis editor.\n* **Project files** - Files from the project within which the analysis is being executed. In JupyterLab, these files appear under the **Project Files** tab in the analysis editor.\n\n## Analysis files\n\nAnalysis files can be added to an analysis in one of the following ways:\n* Uploaded to the analysis directly from the local machine.\n* Downloaded into the analysis directly from a location on the Internet (using **curl** or **wget** in the terminal, for example).\n* Created by clicking the new file creation option in the editor.\n* Produced by the code that is executed during the analysis.\n\nAll files that are created or added in a single run of an analysis are displayed under the **Files** tab in the editor. The image below illustrates how files are displayed in JupyterLab (left) and RStudio (right). \n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/37fb3aa-about_files_in_a_data_cruncher_analysis_1.png\",\n        \"about_files_in_a_data_cruncher_analysis_1.png\",\n        1670,\n        592,\n        \"#f5f5f4\"\n      ]\n    }\n  ]\n}\n[/block]\nAnalysis files are also available at the `/sbgenomics/workspace/<file-name>` path, which can be used to reference the files in the analysis code.\n\n## Project files\n\nProject files are the main focus of an analysis and the reason why Data Cruncher was integrated into the CGC. Thanks to their availability in the editor environment, you can easily reference the files in your code.\n\n### JupyterLab\nThe **Project Files** tab in the editor lists all files that are present in the project within which you are executing your analysis.\n\nAt the top of the list, there is a search box that allows you to filter only project files that match the search criteria. **(1)**\n\nTo reference a project file in your code, you will need to use the full path to the file. The path can be obtained by simply clicking the file in the list, which will copy the path to the clipboard, and pasting the path at the desired place in your code. **(2)** \n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/bbc9ab2-about-files-in-a-data-cruncher-analysis-2.png\",\n        \"about-files-in-a-data-cruncher-analysis-2.png\",\n        1434,\n        694,\n        \"#f1f1f1\"\n      ]\n    }\n  ]\n}\n[/block]\nIf you want to type the path manually, the pattern is `/sbgenomics/project-files/<file-name>`, where `<file-name>` is the name of the project file you wish to reference in your analysis.\n\n### RStudio\nIn RStudio, project files are also referenced using their full path that has the following pattern: `/sbgenomics/project-files/<file-name>` where `<file-name>` is the name of the project file you wish to reference in your analysis.\n\n## Save analysis outputs\n[block:callout]\n{\n  \"type\": \"info\",\n  \"body\": \"Please note that file saving takes place only while the analysis is being stopped. When you click **Stop**, this will trigger the saving process and the analysis status will change to **SAVING**. Once saving has been completed, the analysis status changes to **SAVED**.\"\n}\n[/block]\nOne of the most important aspects of an analysis on the CGC is saving of necessary files produced by the analysis and being able to report them as analysis outputs. The saving method depends on the selected editing environment (JupyterLab or RStudio).\n\n### JupyterLab\nTo save an analysis output file in JupyterLab, you need to right-click it in the list under the **Files** tab in analysis editor and select **Save To Project**. Once the saving process is completed at the end of an analysis run, these files will be available as analysis outputs in the **Produced by this analysis** section in [analysis details](doc:view-and-edit-data-cruncher-analysis-details). Alternatively, you can also copy or move the files to the `/sbgenomics/output-files` folder, which will have the same effect.\n\n### RStudio (beta)\nTo save files as analysis outputs, you need to copy or move them to the `/sbgenomics/output-files` folder. This will also make them available as analysis outputs in the **Produced by this analysis** section in [analysis details](doc:view-and-edit-data-cruncher-analysis-details).","excerpt":"","slug":"about-files-in-a-data-cruncher-analysis","type":"basic","title":"About files in a Data Cruncher analysis"}

About files in a Data Cruncher analysis


The files available in any Data Cruncher analysis belong to one of the following two types: * **Analysis files** - Files produced during the analysis or added to the analysis. These files appear under the **Files** tab in the analysis editor. * **Project files** - Files from the project within which the analysis is being executed. In JupyterLab, these files appear under the **Project Files** tab in the analysis editor. ## Analysis files Analysis files can be added to an analysis in one of the following ways: * Uploaded to the analysis directly from the local machine. * Downloaded into the analysis directly from a location on the Internet (using **curl** or **wget** in the terminal, for example). * Created by clicking the new file creation option in the editor. * Produced by the code that is executed during the analysis. All files that are created or added in a single run of an analysis are displayed under the **Files** tab in the editor. The image below illustrates how files are displayed in JupyterLab (left) and RStudio (right). [block:image] { "images": [ { "image": [ "https://files.readme.io/37fb3aa-about_files_in_a_data_cruncher_analysis_1.png", "about_files_in_a_data_cruncher_analysis_1.png", 1670, 592, "#f5f5f4" ] } ] } [/block] Analysis files are also available at the `/sbgenomics/workspace/<file-name>` path, which can be used to reference the files in the analysis code. ## Project files Project files are the main focus of an analysis and the reason why Data Cruncher was integrated into the CGC. Thanks to their availability in the editor environment, you can easily reference the files in your code. ### JupyterLab The **Project Files** tab in the editor lists all files that are present in the project within which you are executing your analysis. At the top of the list, there is a search box that allows you to filter only project files that match the search criteria. **(1)** To reference a project file in your code, you will need to use the full path to the file. The path can be obtained by simply clicking the file in the list, which will copy the path to the clipboard, and pasting the path at the desired place in your code. **(2)** [block:image] { "images": [ { "image": [ "https://files.readme.io/bbc9ab2-about-files-in-a-data-cruncher-analysis-2.png", "about-files-in-a-data-cruncher-analysis-2.png", 1434, 694, "#f1f1f1" ] } ] } [/block] If you want to type the path manually, the pattern is `/sbgenomics/project-files/<file-name>`, where `<file-name>` is the name of the project file you wish to reference in your analysis. ### RStudio In RStudio, project files are also referenced using their full path that has the following pattern: `/sbgenomics/project-files/<file-name>` where `<file-name>` is the name of the project file you wish to reference in your analysis. ## Save analysis outputs [block:callout] { "type": "info", "body": "Please note that file saving takes place only while the analysis is being stopped. When you click **Stop**, this will trigger the saving process and the analysis status will change to **SAVING**. Once saving has been completed, the analysis status changes to **SAVED**." } [/block] One of the most important aspects of an analysis on the CGC is saving of necessary files produced by the analysis and being able to report them as analysis outputs. The saving method depends on the selected editing environment (JupyterLab or RStudio). ### JupyterLab To save an analysis output file in JupyterLab, you need to right-click it in the list under the **Files** tab in analysis editor and select **Save To Project**. Once the saving process is completed at the end of an analysis run, these files will be available as analysis outputs in the **Produced by this analysis** section in [analysis details](doc:view-and-edit-data-cruncher-analysis-details). Alternatively, you can also copy or move the files to the `/sbgenomics/output-files` folder, which will have the same effect. ### RStudio (beta) To save files as analysis outputs, you need to copy or move them to the `/sbgenomics/output-files` folder. This will also make them available as analysis outputs in the **Produced by this analysis** section in [analysis details](doc:view-and-edit-data-cruncher-analysis-details).