Genome analysis research

The Genomic HyperBrowser

My main research interest has the last years been the development of statistical and algorithmic methodology for large-scale analysis of genomic data. As part of this, I have been a main developer of The Genomic HyperBrowser, which is an open source, web-based software system for statistical analysis. Our ambition is to be a leading system for (statistical) genome analysis, in a synergy with the UCSC/Ensembl genome browsers for storing/retrieving genomic data, with Galaxy for manipulating genomic data, and with EpiExplorer for more explorative analysis of genomic data.

The Genomic HyperBrowser is the result of a tight collaboration between computer scientists, statististicians and biologists in Oslo, Norway. I have from the start been working very closely together with fellow informaticians Sveinung Gundersen and Morten Johansen (and later also Vegard Nygaard and Kai Trengereid), with statistiticans Arnoldo Frigessi, Ingrid Glad, Lars Holden, Marit Holden, Knut Liestøl and Egil Ferkingstad, and with biologists Eivind Hovig, Halfdan Rydbeck, Eivind Tøstesen and Trevor Clancy.

After two years of intense methodology and software development, we published a paper on the HyperBrowser late 2010. With the main infrastructure for genome analysis robustly in place, we are now in a phase where we can effectively build on this base in new directions. We recently published a paper on the disease regulome, a global map of over- and under-representation of 450 transcription factors in 1000 diseases. Also, we recently published a paper on Monte Carlo estimation of p-values in multiple testing settings, and a paper where we distinguish elemental genomic track types and propose a new format for genomic data.

A full list of publications is given at the start page for the group.

Published Aug. 1, 2017 10:47 PM - Last modified Aug. 1, 2017 10:47 PM