Summary: Estimating linkage disequilibrium (LD) is essential for a wide range of summary statistics-based association methods for genome-wide association studies. Large genetic datasets, e.g. the TOPMed WGS project and UK Biobank, enable more accurate and comprehensive LD estimates, but increase the computational burden of LD estimation. Here, we describe emeraLD (Efficient Methods for Estimation and Random Access of LD), a computational tool that leverages sparsity and haplotype structure to estimate LD up to 2 orders of magnitude faster than current tools. Availability and implementation: emeraLD is implemented in C++, and is open source under GPLv3. Source code and documentation are freely available at http://github.com/statgen/emeraLD. Supplementary information: Supplementary data are available at Bioinformatics online.

UNLABELLED: Genotype imputation is a key step in the analysis of genome-wide association studies. Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared with our previous implementation. AVAILABILITY AND IMPLEMENTATION: minimac2, including source code, documentation, and examples is available at http://genome.sph.umich.edu/wiki/Minimac2

SUMMARY: The GWAtoolbox is an R package that standardizes and accelerates the handling of data from genome-wide association studies (GWAS), particularly in the context of large-scale GWAS meta-analyses. A key feature of GWAtoolbox is its ability to perform quality control (QC) of any number of files in a matter of minutes. The implemented workflow has been structured to check three particular data quality aspects: (i) data formatting, (ii) quality of the GWAS results and (iii) data consistency across studies. Output consists of an extensive list of quality statistics and plots which allow inspection of individual files and between-study comparison to identify systematic bias. AVAILABILITY: http://www.eurac.edu/GWAtoolbox CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The study of isolated populations is a promising approach for the identification of genes conferring susceptibility to disease. Due to the complex genealogies of such populations epidemiological studies are challenging.We present ongoing research to using a visual analytics based approach for the identification of diseases that cluster in families, risk factors and heritability patterns.

Spatial proteomic profiling of tissue sections provides in situ molecular analysis of proteins and peptides. Analysis and visualization of these high-dimensional data cubes is challenging. We present a methodology for this task based on a novel developed algorithm for the feature identification and reduction step. To show the validity of our approach, we analyzed prostate cancer tissue sections with an adapted kernel-density based clustering algorithm.

SUMMARY: An efficient tool for mining complex inbred genealogies that identify clusters of individuals sharing the same expected amount of relatedness is described. Additionally it allows for the reconstruction of sub-pedigrees suitable for genetic mapping in a systematic way. AVAILABILITY: http://www.jenti.org.

UNLABELLED: PedVizApi is a Java API (application program interface) for the visual analysis of large and complex pedigrees. It provides all the necessary functionality for the interactive exploration of extended genealogies. While available packages are mostly focused on a static representation or cannot be added to an existing application, PedVizApi is a highly flexible open source library for the efficient construction of visual-based applications for the analysis of family data. An extensive demo application and a R interface is provided. AVAILABILITY: http://www.pedvizapi.org