In this talk I will present the Genomic HyperBrowser (GHB) , a new opensource, web-based, real time inferential machine for sequence-level, bivariate, comparative, local genomic analysis. Sequence-level genomic data consist of annotated pieces of information positioned on locations along the genome. There are thousands of such tracks. We focus on inferential comparison between two tracks at a time, to find local significant aberrations from the null-model behaviour. The output is a context-specific track with levels of significance along the genome. The GHB builds on a simple representation of tracks as random elements on the line and biological hypotheses become stochastic geometric relations. The focus is on local inference, a hierarchical world of 'null models' against which to rigorously assess discoveries by Monte Carlo tests, using an efficient and robust computational system.
Sandve GK, Gundersen S, Rydbeck H, Glad IK, Holden L, Holden M, Liestøl K, Clancy T, Ferkingstad E, Johansen M, Nygaard V, Tøstesen E, Frigessi A, Hovig E, The Genomic HyperBrowser: inferential genomics at the sequence level, Genome Biol 2010, 11:R121