FaST linear mixed models for genome-wide association studies.

We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).

A novel four-caster manual vehicle manoeuvring investigation: Higher loading-weights require larger turning spaces.

Patient-hoists, goods-trolleys and other omni-directional manually operated vehicles are ubiquitous. Yet no substantive, empirically based dynamic analysis has been made of these four-caster vehicles despite manual handling concerns. A relationship between loading-weight and turning space is indicated by theoretical analysis which further shows that this effect is represented by only 11 different manoeuvres. A qualitative account of the theory is presented. These 11 manoeuvres were implemented experimentally. A total of 17 subjects selected a maximum comfortable loading-weight for the four-caster vehicle for each of the 11 manoeuvres. Vehicle displacement and handle forces were measured for different centres of zero velocity. The median loading-weight of the manoeuvre with the highest loading-weight selections was 101% greater than the mean loading-weight of the three manoeuvres with the lowest loading-weight selections. The manoeuvre with the highest loading-weight selections required a larger vehicle turning space: one dimension increased by 37% (173 mm) compared with the three lowest loading-weight selection manoeuvres and the other dimension increased by 17% (130 mm) compared with one of the lowest loading-weight selection manoeuvres. Higher loading-weights require larger turning spaces. These results can contribute to building designs which facilitate safe manual manoeuvring of four-caster vehicles.

An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data.

We present an approach for genome-wide association analysis with improved power on the Wellcome Trust data consisting of seven common phenotypes and shared controls. We achieved improved power by expanding the control set to include other disease cohorts, multiple races, and closely related individuals. Within this setting, we conducted exhaustive univariate and epistatic interaction association analyses. Use of the expanded control set identified more known associations with Crohn's disease and potential new biology, including several plausible epistatic interactions in several diseases. Our work suggests that carefully combining data from large repositories could reveal many new biological insights through increased power. As a community resource, all results have been made available through an interactive web server.