Welcome to the CyVerse Learning Center (beta)¶
The CyVerse Learning center is a beta release of our learning materials in the popular “Read the Docs” formatting. We are transitioning our leaning materials into this format to make them easier to search, use, and update. We will be making regular contributions to these materials and you can suggest new materials or create and share your own. If you have ideas or suggestions please email Tutorials@CyVerse.org. You can also view, edit, and submit contributions on GitHub.
CyVerse offers an interconnected series of platforms, tools and services. These guides will help you navigate the top-level user platforms. If you are new to CyVerse you may wish to Start Here First.
|Discovery Environment||Use hundreds of bioinformatics apps and manage data in the CyVerse Data Store from a simple web interface||Discovery Environment Guide||DE Manual|
|Atmosphere||Cloud computing platform for CyVerse||Atmosphere Guide||Atmosphere Manual|
|Data Store||A unified system for managing and sharing your data across CyVerse’s tools and services||Data Store Guide||Data Store Manual|
|DNA Subway||Educator-focused access to data and informatics tools for modern biology||DNA Subway Guide||See Guide|
|BisQue||Bio-Image Semantic Query User Environment for the exchange and exploration of image data||Coming Soon||BisQue Manual|
|SciApps||A web-based platform for reproducible bioinformatics workflows||SciApps Guide||See Guide|
|Science APIs||CyVerse provides programmatic access to its services through multiple APIs (application programming interfaces), access points with various levels of complexity||Agave Live Docs||See Live Docs|
|VICE||Visual Interactive Computing Environment VICE introduces graphic user interfaces (GUIs) and common Integrated Development Environments (IDEs) such as Project Jupyter Notebooks & Lab, RStudio, Shiny Apps and Linux Desktop||Vice Documentation||See Vice Documentation|
These include short guides through common tasks.
|Create a CyVerse account||User Portal||Start here to create your own account|
|Import data from NCBI SRA using the Discovery Environment||Discovery Environment||The NCBI Sequence Read Archive (SRA) is a repository for high-throughput sequencing reads. These are valuable data for novel analysis and reuse. You can directly import data from SRA into your Data Store using a Discovery Environment app.|
|Evaluate High-throughput Sequencing Reads with FastQC||Discovery Environment||FastQC is a popular tool for evaluating the quality of high-throughput sequencing reads such as from Illumina and PacBio.|
|Filter, Trim, and Process High-throughput Sequencing Reads with Trimmomatic||Discovery Environment||Trimmomatic is a popular application for filtering and trimming high- throughput sequencing reads. Several functions can remove populations of low quality reads, remove sequencing adaptors, and trim low-quality regions of individual reads.|
|EZ installation of popular data science tools||Atmosphere and Jetstream||Install anaconda (Python 2 or 3, R, Jupyter notebooks), Rstudio, Singularity, or Docker easily on any Atmosphere or Jetstream cloud computer (instance).|
|Submit High-throughput Sequencing Reads to NCBI Sequence Read Archive (SRA)||Discovery Environment||The SRA is a canonical repository for sequencing data generated by high-throughput instruments. The CyVerse submission pipeline allows you to directly submit your data into an SRA-linked BioProject.|
|Request a DOI||Data Store, Discovery Environment||Organize your dataset and request a DOI (Digital Object Identifier).|
|Create a Group Project||Data Store, Discovery Environment||Learn the basic steps for setting up a collaborative project using CyVerse.|
These are involved tutorials that cover popular science workflows.
|RNA-Seq with Kallisto and Sleuth||Discovery Environment, Atmosphere||Kallisto is a quick, highly-efficient software for quantifying transcript abundances in an RNA-Seq experiment. Sleuth is designed to analyze and visualize the Kallisto results in R.|
|Genome Annotation with MAKER||SciApps, Discovery Environment||This tutorial is a step-by-step guide for using SciApps to perform MAKER based annotation.|
|Association analysis with mixed models||SciApps||A genome-wide association study (or GWAS) workflow using TASSEL, EMMAX, and MLMM for mixed model analysis.|
These are workshop formatted tutorials that can be used and/or remixed in running your own CyVerse workshop.
|CyVerse Tools and Services Workshop||Discovery Environment, Atmosphere, Data Store||This is a generic agenda and slides for a one-day CyVerse Workshop overviewing the major components of the science infrastrutcure.|
|2018 NEON Data Institute||Discovery Environment, Atmosphere||Provision Atmosphere as a Data Science Workbench running Docker, Singularity, Project Jupyter, and RStudio-Server. The NEON Data Institute 2018 focus is on remote sensing and reproducible workflows in Python and R.|
|CyVerse Container Camp 2019||Discovery Environment, Atmosphere, VICE, Data Store||Topics on container technology for reproducible science.|
|Condensed R: 240-minute tutorial||Discovery Environment, VICE, Data Store||A short introduction to using R and RStudio|
|CyVerse Foundational Open Science Skills 2019||Workshop to train new PIs on advanced cyberinfrastructure||Discovery Environment, Atmosphere, VICE, DataStore|
Contributing to the Learning Center¶
You can contribute to the Learning Center - everything from fixing a typo to adding new documentation pieces.
|Documentation Quickstart||Learning Center||Quick guide to simple contributions and creating new documentation pieces.|
You can contribute to CyVerse - Here are documentation pieces of interest in developing new applications.
|Vice Documentation||VICE||Quick guide to developing for VICE.|
|Creating and Running Docker Containers||Discovery Environment, VICE, Atmosphere||A short guide to Docker and creating your own containerized applications.|
CyVerse Vision: Transforming science through data-driven discovery.
CyVerse Mission: Design, deploy, and expand a national cyberinfrastructure for life sciences research and train scientists in its use. CyVerse provides life scientists with powerful computational infrastructure to handle huge datasets and complex analyses, thus enabling data-driven discovery. Our powerful extensible platforms provide data storage, bioinformatics tools, image analyses, cloud services, APIs, and more.
Originally created under the name iPlant Collaborative as a service to the U.S. plant science communities, CyVerse cyberinfrastructure is relevant to all life sciences disciplines and works equally well on data from plants, animals, or microbes. By democratizing access to supercomputing capabilities, we provide a crucial resource to enable scientists to find solutions for the future. CyVerse is of, by, and for the community, and community-driven needs shape our mission. We rely on your feedback to provide the infrastructure you need most to advance your science, development, and educational agenda.
CyVerse Homepage: http://www.cyverse.org