The immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. We propose a first principled approach to statistical analysis of sequence-level genomic information. We provide a growing collection of generic biological investigations that query pairwise relations between tracks, represented as mathematical objects, along the genome. The Genomic HyperBrowser implements the approach and is available at http://hyperbrowser.uio.no.
@article{arxiv.1101.4898,
title = {The Genomic HyperBrowser: inferential genomics at the sequence level},
author = {Geir K. Sandve and Sveinung Gundersen and Halfdan Rydbeck and Ingrid K. Glad and Lars Holden and Marit Holden and Knut Liestøl and Trevor Clancy and Egil Ferkingstad and Morten Johansen and Vegard Nygaard and Eivind Tøstesen and Arnoldo Frigessi and Eivind Hovig},
journal= {arXiv preprint arXiv:1101.4898},
year = {2011}
}