{"metadata":{"image":[],"title":"","description":""},"api":{"url":"","auth":"required","settings":"","results":{"codes":[]},"params":[]},"next":{"description":"","pages":[]},"title":"Data Cruncher Interactive Analyses","type":"basic","slug":"data-cruncher-interactive-analyses","excerpt":"","body":"## Overview\n\n**Data Cruncher Interactive Analyses** is a public project created with the goal of enhancing end-to-end bioinformatics analysis on the CGC. The suite is currently comprised of the following interactive analyses:\n\n* **Single Cell RNA-Seq Interactive Analysis**. This is an interactive analysis for performing Clustering and Cluster Marker Identification analysis on scRNA-Seq data.\n* **methylKit Differential Methylation Analysis**. This interactive analysis is based on **methylKit**, an R package used for analysis and annotation of DNA methylation information obtained through high-throughput bisulfite sequencing.\n* **NanoStringNorm Gene Expression Analysis**. This analysis is written as an Rmarkdown document and can be used for the normalization, visualization and differential expression of NanoString miRNA and RNA expression level.\n* **Ballgown Interactive Analysis**. This analysis tests for differential expression at the gene and transcript level using FPKM expression measurement data.\n* **VCF Visualization Interactive Analysis**. The analysis offers several quality control analyses of variant call format (VCF) data. It accepts both raw and annotated VCF files without the need for compression or indexing.\n* **Structural Variation (SV) Interactive Analysis**. This is a Jupyter Notebook designed for a quick overview of a VCF file containing structural variant calls. The analysis parses the SV caller’s VCF output for simple data filtering and visualization.\n* **ChIP-seq Interactive Analysis**. The Chromatin Immunoprecipitation Sequencing (ChIP-Seq) Interactive Analysis provides a visualization of the likely locations of transcription factor binding sites or histone modifications.\n* **Microbiome Differential Abundance Analysis**. The goal of the Microbiome Differential Abundance Interactive Analysis is to detect differential abundance of microbes between two predetermined classes of samples. This experimental design is applicable to case-control clinical studies and other settings for which there is prior assumption about the existing microbiological conditions within the different groups of samples.\n\n## Access and run an analysis\n1. On the main menu bar click **Public projects**.\n2. Select **Data Cruncher Interactive Analyses**.\n3. Once in the public project, click the info icon next to the project title. Project information box is displayed.\n4. In the bottom-right part of the project information box, click **Copy project**.\n5. If needed, change the project name, url, billing group or [execution settings](doc:modify-project-settings#section-modify-execution-settings).\n6. Click **Copy**. You are now taken to your own copy of the **Data Cruncher Interactive Analyses** public project.\n7. In the top-right corner click **Interactive Analysis**.\n8. On the **Data Cruncher** card click **Open**. You see a list of all available interactive analyses.\n9. Click the name of the desired analysis.\n10. Click **Start** in the top-right corner. Your analysis will start initializing.\n11. Once it is ready, click **Open in editor** in the top-right corner. This opens the JupyterLab editor.\n12. In the files list on the left, double click the **.ipynb** file containing the analysis. Your analysis is now loaded in the editor and ready to be executed.\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/0b0a590-sbpla-data-cruncher-interactive-analyses-1.png\",\n        \"sbpla-data-cruncher-interactive-analyses-1.png\",\n        1093,\n        706,\n        \"#efedec\"\n      ]\n    }\n  ]\n}\n[/block]","updates":[],"order":9,"isReference":false,"hidden":false,"sync_unique":"","link_url":"","link_external":false,"_id":"5f2d32b2672d9805d23f730d","createdAt":"2020-08-07T10:53:38.702Z","user":"5767bc73bb15f40e00a28777","category":{"sync":{"isSync":false,"url":""},"pages":[],"title":"PUBLIC PROJECTS","slug":"public-projects","order":7,"from_sync":false,"reference":false,"_id":"5771811e27a5c20e00030dcd","version":"55faf11ba62ba1170021a9aa","__v":0,"project":"55faf11ba62ba1170021a9a7","createdAt":"2016-06-27T19:40:14.237Z"},"version":{"version":"1.0","version_clean":"1.0.0","codename":"","is_stable":true,"is_beta":true,"is_hidden":false,"is_deprecated":false,"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","5db6f03a6e187c006f667fa4","5f894c7d3b0894006477ca01"],"_id":"55faf11ba62ba1170021a9aa","releaseDate":"2015-09-17T16:58:03.490Z","createdAt":"2015-09-17T16:58:03.490Z","project":"55faf11ba62ba1170021a9a7","__v":47},"project":"55faf11ba62ba1170021a9a7","__v":0,"parentDoc":null}

Data Cruncher Interactive Analyses


## Overview **Data Cruncher Interactive Analyses** is a public project created with the goal of enhancing end-to-end bioinformatics analysis on the CGC. The suite is currently comprised of the following interactive analyses: * **Single Cell RNA-Seq Interactive Analysis**. This is an interactive analysis for performing Clustering and Cluster Marker Identification analysis on scRNA-Seq data. * **methylKit Differential Methylation Analysis**. This interactive analysis is based on **methylKit**, an R package used for analysis and annotation of DNA methylation information obtained through high-throughput bisulfite sequencing. * **NanoStringNorm Gene Expression Analysis**. This analysis is written as an Rmarkdown document and can be used for the normalization, visualization and differential expression of NanoString miRNA and RNA expression level. * **Ballgown Interactive Analysis**. This analysis tests for differential expression at the gene and transcript level using FPKM expression measurement data. * **VCF Visualization Interactive Analysis**. The analysis offers several quality control analyses of variant call format (VCF) data. It accepts both raw and annotated VCF files without the need for compression or indexing. * **Structural Variation (SV) Interactive Analysis**. This is a Jupyter Notebook designed for a quick overview of a VCF file containing structural variant calls. The analysis parses the SV caller’s VCF output for simple data filtering and visualization. * **ChIP-seq Interactive Analysis**. The Chromatin Immunoprecipitation Sequencing (ChIP-Seq) Interactive Analysis provides a visualization of the likely locations of transcription factor binding sites or histone modifications. * **Microbiome Differential Abundance Analysis**. The goal of the Microbiome Differential Abundance Interactive Analysis is to detect differential abundance of microbes between two predetermined classes of samples. This experimental design is applicable to case-control clinical studies and other settings for which there is prior assumption about the existing microbiological conditions within the different groups of samples. ## Access and run an analysis 1. On the main menu bar click **Public projects**. 2. Select **Data Cruncher Interactive Analyses**. 3. Once in the public project, click the info icon next to the project title. Project information box is displayed. 4. In the bottom-right part of the project information box, click **Copy project**. 5. If needed, change the project name, url, billing group or [execution settings](doc:modify-project-settings#section-modify-execution-settings). 6. Click **Copy**. You are now taken to your own copy of the **Data Cruncher Interactive Analyses** public project. 7. In the top-right corner click **Interactive Analysis**. 8. On the **Data Cruncher** card click **Open**. You see a list of all available interactive analyses. 9. Click the name of the desired analysis. 10. Click **Start** in the top-right corner. Your analysis will start initializing. 11. Once it is ready, click **Open in editor** in the top-right corner. This opens the JupyterLab editor. 12. In the files list on the left, double click the **.ipynb** file containing the analysis. Your analysis is now loaded in the editor and ready to be executed. [block:image] { "images": [ { "image": [ "https://files.readme.io/0b0a590-sbpla-data-cruncher-interactive-analyses-1.png", "sbpla-data-cruncher-interactive-analyses-1.png", 1093, 706, "#efedec" ] } ] } [/block]