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  • The Barbara K. Ostrom (1978) Bioinformatics and Computing Facility
  • Computing Resources
    • Active Data Storage
    • Archive Data Storage
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    • Other Resources
  • Bioinformatics Topics
    • Tools - A Basic Bioinformatics Toolkit
      • Getting more out of Microsoft Excel
      • Bioinformatics Applications of Unix
        • Unix commands applied to bioinformatics
        • Manipulate NGS files using UNIX commands
        • Manipulate alignment files using UNIX commands
      • Alignments and Mappers
      • Relational databases
        • Running Joins on Galaxy
      • Spotfire
    • Tasks - Bioinformatics Methods
      • UCSC Genome Bioinformatics
        • Interacting with the UCSC Genome Browser
        • Obtaining DNA sequence from the UCSC Database
        • Obtaining genomic data from the UCSC database using table browser queries
        • Filtering table browser queries
        • Performing a BLAT search
        • Creating Custom Tracks
        • UCSC Intersection Queries
        • Viewing cross-species alignments
        • Galaxy
          • Intro to Galaxy
          • Galaxy NGS Illumina QC
          • Galaxy NGS Illumina SE Mapping
          • Galaxy SNP Interval Data
        • Editing and annotation gene structures with Argo
      • GeneGO MetaCore
        • GeneGo Introduction
        • Loading Data Into GeneGO
        • Data Management in GeneGO
        • Setting Thresholds and Background Sets
        • Search And Browse Content Tab
        • Workflows and Reports Tab
        • One-click Analysis Tab
        • Building Network for Your Experimental Data
      • Functional Annotation of Gene Lists
      • Multiple Sequence Alignment
        • Clustalw2
      • Phylogenetic analysis
        • Neighbor Joining method in Phylip
      • Microarray data processing with R/Bioconductor
    • Running Jupyter notebooks on luria cluster nodes
  • Data Management
    • Globus
  • Mini Courses
    • Schedule
      • Previous Teaching
    • Introduction to Unix and KI Computational Resources
      • Basic Unix
        • Why Unix?
        • The Unix Tree
        • The Unix Terminal and Shell
        • Anatomy of a Unix Command
        • Basic Unix Commands
        • Output Redirection and Piping
        • Manual Pages
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        • Unix Text Editors
          • nano
          • vi / vim
          • emacs
        • Shell Scripts
      • Software Installation
        • Module
        • Conda Environment
      • Slurm
    • Introduction to Unix
      • Why Unix?
      • The Unix Filesystem
        • The Unix Tree
        • Network Filesystems
      • The Unix Shell
        • About the Unix Shell
        • Unix Shell Manual Pages
        • Using the Unix Shell
          • Viewing the Unix Tree
          • Traversing the Unix Tree
          • Editing the Unix Tree
          • Searching the Unix Tree
      • Files
        • Viewing File Contents
        • Creating and Editing Files
        • Manipulating Files
        • Symbolic Links
        • File Ownership
          • How Unix File Ownership Works
          • Change File Ownership and Permissions
        • File Transfer (in-progress)
        • File Storage and Compression
      • Getting System Information
      • Writing Scripts
      • Schedule Scripts Using Crontab
    • Advanced Utilization of IGB Computational Resources
      • High Performance Computing Clusters
      • Slurm
        • Checking the Status of Computing Nodes
        • Submitting Jobs / Slurm Scripts
        • Interactive Sessions
      • Package Management
        • The System Package Manager
        • Environment Modules
        • Conda Environments
      • SSH Port Forwarding
        • SSH Port Forwarding Jupyter Notebooks
      • Containerization
        • Docker
          • Docker Installation
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          • Building Docker Images
        • Singularity
          • Differences from Docker
          • Running Images in Singularity
      • Running Nextflow / nf-core Pipelines
    • Python
      • Introduction to Python for Biologists
        • Interactive Python
        • Types
          • Strings
          • Lists
          • Tuples
          • Dictionaries
        • Control Flow
        • Loops
          • For Loops
          • While Loops
        • Control Flows and Loops
        • Storing Programs for Re-use
        • Reading and Writing Files
        • Functions
      • Biopython
        • About Biopython
        • Quick Start
          • Basic Sequence Analyses
          • SeqRecord
          • Sequence IO
          • Exploration of Entrez Databases
        • Example Projects
          • Coronavirus Exploration
          • Translating a eukaryotic FASTA file of CDS entries
        • Further Resources
      • Machine Learning with Python
        • About Machine Learning
        • Hands-On
          • Project Introduction
          • Supervised Approaches
            • The Logistic Regression Model
            • K-Nearest Neighbors
          • Unsupervised Approaches
            • K-Means Clustering
          • Further Resources
      • Data Processing with Python
        • Pandas
          • About Pandas
          • Making DataFrames
          • Inspecting DataFrames
          • Slicing DataFrames
          • Selecting from DataFrames
          • Editing DataFrames
        • Matplotlib
          • About Matplotlib
          • Basic Plotting
          • Advanced Plotting
        • Seaborn
          • About Seaborn
          • Basic Plotting
          • Visualizing Statistics
          • Visualizing Proteomics Data
          • Visualizing RNAseq Data
    • R
      • Intro to R
        • Before We Start
        • Getting to Know R
        • Variables in R
        • Functions in R
        • Data Manipulation
        • Simple Statistics in R
        • Basic Plotting in R
        • Advanced Plotting in R
        • Writing Figures to a File
        • Further Resources
    • Version Control with Git
      • About Version Control
      • Setting up Git
      • Creating a Repository
      • Tracking Changes
        • Exercises
      • Exploring History
        • Exercises
      • Ignoring Things
      • Remotes in Github
      • Collaborating
      • Conflicts
      • Open Science
      • Licensing
      • Citation
      • Hosting
      • Supplemental
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  1. Mini Courses
  2. Version Control with Git

Hosting

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Last updated 1 year ago

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About Hosting

The second big question for groups that want to open up their work is where to host their code and data. One option is for the lab, the department, or the university to provide a server, manage accounts and backups, and so on. The main benefit of this is that it clarifies who owns what, which is particularly important if any of the material is sensitive (i.e., relates to experiments involving human subjects or may be used in a patent application). The main drawbacks are the cost of providing the service and its longevity: a scientist who has spent ten years collecting data would like to be sure that data will still be available ten years from now, but that’s well beyond the lifespan of most of the grants that fund academic infrastructure.

Another option is to purchase a domain and pay an Internet service provider (ISP) to host it. This gives the individual or group more control, and sidesteps problems that can arise when moving from one institution to another, but requires more time and effort to set up than either the option above or the option below.

The third option is to use a public hosting service like , , or . Each of these services provides a web interface that enables people to create, view, and edit their code repositories. These services also provide communication and project management tools including issue tracking, wiki pages, email notifications, and code reviews. These services benefit from economies of scale and network effects: it’s easier to run one large service well than to run many smaller services to the same standard. It’s also easier for people to collaborate. Using a popular service can help connect your project with communities already using the same service.

As an example, Software Carpentry where you can find the . Anyone with a GitHub account can suggest changes to this text.

GitHub repositories can also be assigned DOIs, . For example, is the DOI that has been “minted” for this introduction to Git.

Using large, well-established services can also help you quickly take advantage of powerful tools. One such tool, continuous integration (CI), can automatically run software builds and tests whenever code is committed or pull requests are submitted. Direct integration of CI with an online hosting service means this information is present in any pull request, and helps maintain code integrity and quality standards. While CI is still available in self-hosted situations, there is much less setup and maintenance involved with using an online service. Furthermore, such tools are often provided free of charge to open source projects, and are also available for private repositories for a fee.

  • Institutional Barriers

Sharing is the idea for science, but many institutions place restrictions on sharing, for example to protect potentially patentable intellectual property. If you encounter such restrictions, it can be productive to inquire about the underlying motivations and either to request an exception for a specific project or domain, or to push more broadly for institutional reform to support more open science.

  • Can My Work Be Public?

Find out whether you are allowed to host your work openly in a public repository. Can you do this unilaterally, or do you need permission from someone in your institution? If so, who?

  • Where Can I Share My Work?

Does your institution have a repository or repositories that you can use to share your papers, data and software? How do institutional repositories differ from services like , , or ?

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