Conor Lawless

21 November 2017

Visualising correlation in an AR(1) process

Autoregression models are a type of stochastic, dynamic process. They are a mathematical representation of some value that varies with time, where the variation includes a random, unpredictable component. Using a computer to generate (pseudo-)random numbers, we can generate a set of simulated values across time that are consistent with this kind of model. Stochastic simulations aim to capture the random component in the process and so are usually different every time they’re run. ... Read more

11 October 2017

Quantifying the strength & significance of genetic interactions

Recently, I have been analysing some functional genomics and drug screen datasets. The techniques I use are similar to those I developed while working on and using a method called Quantitative Fitness Analysis (QFA) (Addinall et al. (2011), Lawless et al. (2010)). QFA is a method for screening the health of up to tens of thousands of microbial cell populations (examples in picture above). It is typically used to search for genes interacting with a gene of particular interest. ... Read more

11 April 2017

Interactive plots for comparing simulated output from simulation models: scientific computing & javascript

In a previous post , I used the interactive plot below to visualise & compare population growth curves simulated from three members of a family of models that share the same set of parameters. The user can adjust parameter values and explore the resulting changes in similarities and differences between simulations from the three models in real time. In this post I will discuss where dynamic visualisation of quantitative analysis is most useful and how the calculations underlying this analysis were carried out in JavaScript. ... Read more