MOTIVATION: A plethora of sequenced and genotyped disease cohorts is available to the biomedical research community, spread across many portals and represented in various formats. RESULTS: We have gathered several large studies, including GERA and GRU, and computed population- and disease-specific genetic variant frequencies. In total, our portal provides fast access to genetic variants observed in 84,928 individuals from 39 disease populations. We also include 66,335 controls, such as the 1000 Genomes and Scripps Wellderly. CONCLUSION: Combining multiple studies helps validate disease-associated variants in each underlying data set, detect potential false positives using frequencies of control populations, and identify novel candidate disease-causing alterations in known or suspected genes. AVAILABILITY AND IMPLEMENTATION: https://rvs.u.hpc.mssm.edu/divas CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Data from a plethora of high-throughput sequencing studies is readily available to researchers, providing genetic variants detected in a variety of healthy and disease populations. While each individual cohort helps gain insights into polymorphic and disease-associated variants, a joint perspective can be more powerful in identifying polymorphisms, rare variants, disease-associations, genetic burden, somatic variants, and disease mechanisms. DESCRIPTION: We have set up a Reference Variant Store (RVS) containing variants observed in a number of large-scale sequencing efforts, such as 1000 Genomes, ExAC, Scripps Wellderly, UK10K; various genotyping studies; and disease association databases. RVS holds extensive annotations pertaining to affected genes, functional impacts, disease associations, and population frequencies. RVS currently stores 400 million distinct variants observed in more than 80,000 human samples. CONCLUSIONS: RVS facilitates cross-study analysis to discover novel genetic risk factors, gene-disease associations, potential disease mechanisms, and actionable variants. Due to its large reference populations, RVS can also be employed for variant filtration and gene prioritization. AVAILABILITY: A web interface to public datasets and annotations in RVS is available at https://rvs.u.hpc.mssm.edu/.

Mining gene expression profiles has proven valuable for identifying signatures serving as surrogates of cancer phenotypes. However, the similarities of such signatures across different cancer types have not been strong enough to conclude that they represent a universal biological mechanism shared among multiple cancer types. Here we present a computational method for generating signatures using an iterative process that converges to one of several precise attractors defining signatures representing biomolecular events, such as cell transdifferentiation or the presence of an amplicon. By analyzing rich gene expression datasets from different cancer types, we identified several such biomolecular events, some of which are universally present in all tested cancer types in nearly identical form. Although the method is unsupervised, we show that it often leads to attractors with strong phenotypic associations. We present several such multi-cancer attractors, focusing on three that are prominent and sharply defined in all cases: a mesenchymal transition attractor strongly associated with tumor stage, a mitotic chromosomal instability attractor strongly associated with tumor grade, and a lymphocyte-specific attractor.

Low power has become a burning issue in modern VLSI design. To deal with this problem, the multiple-supply voltage (MSV) is a technique widely applied to a design to reduce its power consumption. However, there exist several challenges in implementing Multi-Voltage designs, which includes floorplanning, level-shifter placement, and power planning [5]. Among these challenges, placement of level shifters has direct impacts on the chip area, total wirelength, and power planning. Although several works considering MSV driven floorplanning have been proposed, they do not actually place level shifters in their flows, which makes their results unrealistic. Yu et al. [19] first proposed a methodology to place level shifters during floorplanning. But, level shifters are inserted in the whitespace of a chip, which would increase wirelength of long wires and make power planning more difficult. Thus, in this paper, we first propose two ways to allocate regions for level shifters during floorplanning, and then give a two-stage approach to place these level shifters at proper locations. The experimental results reveal that the wirelength is underestimated if we do place level shifters and it can obtain smaller wirelength if we can consider level shifters during floorplanning.