The Genomic HyperBrowser: inferential genomics at the sequence level

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

Proglacial icings as indicators of glacier thermal regime : ice thickness changes and icing occurrence in Svalbard

Proglacial icings (also known as naled or aufeis) are frequently observed in the forefields of polar glaciers. Their formation has been ascribed to the refreezing of upwelling groundwater that has originated from subglacial melt, and thus the presence of icings has been used as evidence of polythermal glacier regime. We provide an updated analysis of icing occurrence in Svalbard and test the utility of icings as an indicator of thermal regime by comparing icing presence with: (1) mean glacier thickness, as a proxy for present thermal regime; and (2) evidence of past surge activity, which is an indicator of past thermal regime. A total of 279 icings were identified from TopoSvalbard imagery covering the period 2008-2012, of which 143 corresponded to icings identified by Bukowska-Jania and Szafraniec (2005) from aerial photographs from 1990. Only 46% of icings observed in 2008-2012 were found to occur at glaciers with thicknesses consistent with a polythermal regime, meaning a large proportion were associated with glaciers predicted to be of a cold or transitional thermal regime. As a result, icing presence alone may be an unsuitable indicator of glacier regime. We further found that, of the 279 glaciers with icings, 63% of cold-based glaciers and 64% of transitional glaciers were associated with evidence of surge activity. We therefore suggest that proglacial icing formation in Svalbard may reflect historical (rather than present) thermal regime, and that icings possibly originate from groundwater effusion from subglacial taliks that persist for decades following glacier thinning and associated regime change

Comparison of the Agilent, ROMA/NimbleGen and Illumina platforms for classification of copy number alterations in human breast tumors

<p>Abstract</p> <p>Background</p> <p>Microarray Comparative Genomic Hybridization (array CGH) provides a means to examine DNA copy number aberrations. Various platforms, brands and underlying technologies are available, facing the user with many choices regarding platform sensitivity and number, localization, and density distribution of probes.</p> <p>Results</p> <p>We evaluate three different platforms presenting different nature and arrangement of the probes: The Agilent Human Genome CGH Microarray 44 k, the ROMA/NimbleGen Representational Oligonucleotide Microarray 82 k, and the Illumina Human-1 Genotyping 109 k BeadChip, with Agilent being gene oriented, ROMA/NimbleGen being genome oriented, and Illumina being genotyping oriented. We investigated copy number changes in 20 human breast tumor samples representing different gene expression subclasses, using a suite of graphical and statistical methods designed to work across platforms. Despite substantial differences in the composition and spatial distribution of probes, the comparison revealed high overall concordance. Notably however, some short amplifications and deletions of potential biological importance were not detected by all platforms. Both correlation and cluster analysis indicate a somewhat higher similarity between ROMA/NimbleGen and Illumina than between Agilent and the other two platforms. The programs developed for the analysis are available from <url>http://www.ifi.uio.no/bioinf/Projects/</url>.</p> <p>Conclusion</p> <p>We conclude that platforms based on different technology principles reveal similar aberration patterns, although we observed some unique amplification or deletion peaks at various locations, only detected by one of the platforms. The correct platform choice for a particular study is dependent on whether the appointed research intention is gene, genome, or genotype oriented.</p

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data

We introduce a wide and deep neural network for prediction of progression from patients with mild cognitive impairment to Alzheimer's disease. Information from anatomical shape and tabular clinical data (demographics, biomarkers) are fused in a single neural network. The network is invariant to shape transformations and avoids the need to identify point correspondences between shapes. To account for right censored time-to-event data, i.e., when it is only known that a patient did not develop Alzheimer's disease up to a particular time point, we employ a loss commonly used in survival analysis. Our network is trained end-to-end to combine information from a patient's hippocampus shape and clinical biomarkers. Our experiments on data from the Alzheimer's Disease Neuroimaging Initiative demonstrate that our proposed model is able to learn a shape descriptor that augments clinical biomarkers and outperforms a deep neural network on shape alone and a linear model on common clinical biomarkers.Comment: Data and Machine Learning Advances with Multiple Views Workshop, ECML-PKDD 201

Breast cancer incidence in food- vs non-food-producing areas in Norway: possible beneficial effects of World War II

It has been suggested that World War II influenced breast cancer risk among Norwegian women by affecting adolescent growth. Diet changed substantially during the war, and the reduction in energy intake was assumed to be larger in non-food- producing than in food-producing municipalities. In the present study, we have looked at the influence of residential history in areas with and without food production on the incidence of breast cancer in a population-based cohort study consisting of 597 906 women aged between 30 and 64 years. The study included 7311 cases of breast cancer, diagnosed between 1964 and 1992. The risk estimates were calculated using a Poisson regression model. The results suggest that residential history may influence the risk of breast cancer, where the suggested advantageous effect of World War II seems to be larger in non-food-producing than in food-producing areas. Breast cancer incidence was observed to decline for the post-war cohorts, which is discussed in relation to diet