{"_id":"58f5d537df3d1137004d5c8e","user":"5767bc73bb15f40e00a28777","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"},"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":31,"slug":"data-cruncher","title":"DATA CRUNCHER (ADVANCE ACCESS)"},"project":"55faf11ba62ba1170021a9a7","__v":0,"parentDoc":null,"updates":[],"next":{"pages":[],"description":""},"createdAt":"2017-04-18T08:58:31.062Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":0,"body":"## Bring interactive analysis to your data\n\nData Cruncher is an interactive analysis tool on the CGC for exploring and mining data using Jupyter notebooks. The Data Cruncher complements other tools for data exploration including [the Genome Browser](doc:seven-bridges-genome-browser).\n\nBioinformatics analyses rarely complete with the execution of a workflow and results often need to be further analyzed. In most cases, the size of the data makes it impossible (or at least very impractical) to download results and perform further analysis on a local machine. Instead, Data Cruncher brings the analytical tool to your data, integrating the two within the CGC. When you need to run a few very simple shell commands to explore data or perform a more complex analysis using Python, R or Julia, Data Cruncher will enable you to do it directly on the CGC, thus avoiding the time and resource consuming process of downloading data to the local machine.\n\nKey features of Data Cruncher are:\n\n* Supports Python, R and Julia programming languages.\n* Allows you to perform analyses directly where your data is.\n* Is tightly integrated with the CGC.\n* Uses JupyterLab as the computational environment.\n* Allows you to save outputs of analyses to your projects on the CGC.\n\n## Terms and concepts\n\nBelow is a list of terms that will help you understand the key concepts and technologies behind Data Cruncher.\n\n* **Analysis** - A way of organizing notebooks, scripts, and files to meaningfully represent one unit of work. An analysis is an integral part of a project on the CGC.\n* **Editor** - The environment where you edit the analysis code and additional text content, access project and analysis files, reference them in your code and execute the analysis.\n* **Notebook** - A document consisting of ordered input and output cells which can contain code, plots or text.\n* **Kernel** - The engine that executes the code entered in a notebook. Currently, Data Cruncher supports execution of Python, R and Julia code.\n* **Session** - A single run of an analysis, from the initialization of the server instance to run the analysis on, until the analysis is stopped and saved.","excerpt":"","slug":"about-data-cruncher","type":"basic","title":"About Data Cruncher"}

About Data Cruncher


## Bring interactive analysis to your data Data Cruncher is an interactive analysis tool on the CGC for exploring and mining data using Jupyter notebooks. The Data Cruncher complements other tools for data exploration including [the Genome Browser](doc:seven-bridges-genome-browser). Bioinformatics analyses rarely complete with the execution of a workflow and results often need to be further analyzed. In most cases, the size of the data makes it impossible (or at least very impractical) to download results and perform further analysis on a local machine. Instead, Data Cruncher brings the analytical tool to your data, integrating the two within the CGC. When you need to run a few very simple shell commands to explore data or perform a more complex analysis using Python, R or Julia, Data Cruncher will enable you to do it directly on the CGC, thus avoiding the time and resource consuming process of downloading data to the local machine. Key features of Data Cruncher are: * Supports Python, R and Julia programming languages. * Allows you to perform analyses directly where your data is. * Is tightly integrated with the CGC. * Uses JupyterLab as the computational environment. * Allows you to save outputs of analyses to your projects on the CGC. ## Terms and concepts Below is a list of terms that will help you understand the key concepts and technologies behind Data Cruncher. * **Analysis** - A way of organizing notebooks, scripts, and files to meaningfully represent one unit of work. An analysis is an integral part of a project on the CGC. * **Editor** - The environment where you edit the analysis code and additional text content, access project and analysis files, reference them in your code and execute the analysis. * **Notebook** - A document consisting of ordered input and output cells which can contain code, plots or text. * **Kernel** - The engine that executes the code entered in a notebook. Currently, Data Cruncher supports execution of Python, R and Julia code. * **Session** - A single run of an analysis, from the initialization of the server instance to run the analysis on, until the analysis is stopped and saved.