Bio-Linux. Now available in the Cloud

For some time now, NERC has been providing us with Bio-Linux. If you don’t want to be bothered with installing all the essential bioinformatic software for your Ubuntu box, you can install Bio-Linux, either as a a Linux distro for installation from scratch, or as a set of packages for an already existing Debian or Ubuntu workstation. Biolinux comes complete with EMBOSS, NCBI Tools (BLAST and BLAST+ included) , various nextgen and metagenomic sequence processing software (ampliconoise, fastqc, MIRA, mothur), annotation pipelines (glimmer3, yamap), tree building and visualization (forester, phylip. treeview, njplot), bio{python|perl|ruby|java}, and an incredible amount of many more goodies.

Now, from the people who brought you Bio-Linux, there is CloudBioLinux. I haven’t checked it out yet, but it sounds pretty cool. If you need cloud computing resources, and you don’t have your own cluster (or you do and you just want to supplement it), you have a read-made package for massive data analysis. All under an open-source license, with the ability to fork your own in their GitHub repository. From the page:


Many bioinformatics workflows involve large datasets in which high performance computing is needed. Cloud computing provides researchers with the ability to perform computations using a practically unlimited pool of virtual machines, using platforms such as Amazon EC2Eucalyptus or VirtualBox. CloudBioLinux utilizes these resources to enable instant access to biological software, programming libraries and data.

CloudBioLinux is a community project and we welcome contributors and feedback. Software and data are built using Fabric for fully automated installation and deployment. Packages are specified in simpleconfiguration files for both Linux packages and programming language libraries. Please fork our code on GitHub and suggest improvements and additions.

These resources are designed for biologists as well as programmers. With the help of the NEBC Bio-Linux development team, images include the biological software and libraries available in local installations along with a FreeNX desktop environment designed to ease the transition to remote computational analysis.



Of course, there is this prescient and insightful song about cloud computing resource management:


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