Resources

Looking to tackle large datasets?

 

 

 

 

 

 

 

The Advanced Research and Computing Center (ARCC) offers free(!!) user accounts on its computer resource (MtMoran) for those interested in undertaking computationally intensive analysis of genetic data.

Once you have an account for MtMoran, you can request to have INBRE Condo status (click here) for your account.

Condo access includes:

  • Highest priority access to the 20 fat nodes that comprise the INBRE condo maintained and supported by the ARCC.
    1. 128GB RAM per node
    2. 10 nodes with 2, 8-core processors per node 
    3. 10 nodes with 32-Core (2.1 GHz, 3.0 Turbo), 240 GB local SSD, InfiniBand Haswell
  • Exclusive access to hugemem, 1024TB RAM nodes that are useful for de novo genome assembly from fragment reads, and complex phylogenetic reconstructions
    1. 1 node, single 8-core, 3.5 GHz
    2. 2 nodes,  32-Core (2.1 GHz, 3.0 Turbo), 240 GB local SSD, InfiniBand Haswel
  • Technical support from ARCC with regards to software and interacting with Mount Moran
  • Informatics support from the INBRE Bioinformatics Core.

 

 

 

 

 

 

If you would prefer to work locally (on your own machine), let us know and we can help you get setup for that too. In most cases, end users can find everything they need for manipulation and analysis by downloading and installing the suite of open sourced tools that are part of the latest BioBuilds release.

 

 

Need training? Write us and let us know what you need, we offer tailored workshops/training sessions for the INBRE community. If we can't help you, we also offer funding to attend workshops for you to obtain training.

If you are interested in the the range of training available, consider the following (many more not listed):

Subscribe to EvolDir and receive info on courses and workshops (instuctions for subscription). This is by far the most comprehensive email resource.

UCDavis runs a a ongoing series of training courses. Cold Spring Harbor Labs offers a similar suite of courses as does Columbia University.

 

Want to do it yourself? Consider one of the many online tutorial offerings such as EMBL, coding the hard way (all sorts of coding), or Python for Biologists (python introduction)