Fast and accurate exhaustive higher-order epistasis search with BitEpi.

Complex genetic diseases may be modulated by a large number of epistatic interactions affecting a polygenic phenotype. Identifying these interactions is difficult due to computational complexity, especially in the case of higher-order interactions where more than two genomic variants are involved. In this paper, we present BitEpi, a fast and accurate method to test all possible combinations of up to four bi-allelic variants (i.

INSIDER: alignment-free detection of foreign DNA sequences.

External DNA sequences can be inserted into an organism's genome either through natural processes such as gene transfer, or through targeted genome engineering strategies. Being able to robustly identify such foreign DNA is a crucial capability for health and biosecurity applications, such as anti-microbial resistance (AMR) detection or monitoring gene drives. This capability does not exist for poorly characterised host genomes or with limited information about the integrated sequence.

Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data.

Device-based assessments are frequently used to measure physical activity (PA) but contextual measures are often lacking. There is a need for new methods, and one under-explored option is the use of wearable cameras. This study tested the use of wearable cameras in PA measurement by comparing intensity classifications from accelerometers with wearable camera data.

Using wearable cameras to monitor eating and drinking behaviours during transport journeys.

Purpose: Young adults are vulnerable to weight gain and dietary behaviours such as 'eating on the run' are likely contributors. The objective of this study was to examine eating and drinking behaviours during transport journeys in a sample of young adults using wearable cameras that take continuous images every 30 s.

Methods: Seventy-eight 18-30 year olds wore an Autographer wearable camera for three consecutive days.

VariantSpark: Cloud-based machine learning for association study of complex phenotype and large-scale genomic data.

Background: Many traits and diseases are thought to be driven by >1 gene (polygenic). Polygenic risk scores (PRS) hence expand on genome-wide association studies by taking multiple genes into account when risk models are built. However, PRS only considers the additive effect of individual genes but not epistatic interactions or the combination of individual and interacting drivers.

Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak.

Pre-clinical responses to fast-moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g.

Macronutrient intakes and the lifespan-fecundity trade-off: a geometric framework agent-based model.

Lifespan and fecundity, the main components in evolutionary fitness, are both strongly affected by nutritional state. Geometric framework of nutrition (GFN) experiments has shown that lifespan and fecundity are separated in nutrient space leading to a functional trade-off between the two traits. Here we develop a spatially explicit agent-based model (ABM) using the GFN to explore how ecological factors may cause selection on macronutrient appetites to optimally balance these life-history traits.