Emerging Tools and Techniques Using Computational Pipelines and Results with NDAR

Background: We will provide instruction on how to best access the wealth of data now available in NDAR, filtering across omics, clinical, and neuro-signal recordings results and how these data can then be organized specific to a publication or computational result. Objectives: the dynamic filtering of data by most any attribute (e.g. IQ, ADI score, omic alteration, phenotype, or neuro-signal recordings result) in NDAR across numerous repositories offers opportunity for iterative data exploration.  This ability, coupled with emerging computational pipelines and analytical tools being actively integrated with NDAR will be presented.  Methods: the different approaches available for query/inspection of NDAR data using massively parallel computational capabilities in the cloud or institutional computational environments will be presented.  How best to leverage these resources will be discussed.   Results: NDAR allows data, methods, software, and the computational environment to be easily searched and applied to subsets of data that are of interest to an autism researcher.  The ability to re-analyze data with small changes to the analysis parameters and to track all of those results, the software and methods used is an emerging area of scientific discovery.  Conclusions: Cloud computing is now allowing analysis on a scale never before possible.  The techniques used and analysis performed is now shared in a common location and can be made available  to others.   Learning how to use these very powerful tools and techniques for scientific discovery will be provided.