Biology subjects

Stephen J Eglen

Publications and source records attributed to Stephen J Eglen.

4 recordsLinked to original sources

bioRxiv2016

Ten Simple Rules for Taking Advantage of git and GitHub

A Ten Simple Rules guide to git and GitHub. We describe and provide examples on how to use these software to track projects, as users, teams and organizations. We document collaborative development using branching and forking, interaction between collaborators using issues and continuous integration and automation using, for example, Travis CI and codevoc. We also describe dissemination and social aspects of GitHub such as GitHub pages, following and watching repositories, and give advice on how to make code citable.

Bioinformatics↗

bioRxiv2016

A Bayesian framework for comparing the structure of spontaneous correlated activity recorded under different conditions

Distant-dependent correlations in spontaneous retinal activity are thought to be instructive in the development of the retinotopic map and eye-specific segregation maps. Many studies which seek to investigate these correlations and their role in map formation record spontaneous retinal activity from different pheno-types or experimental conditions and compare the distance-dependence of the correlations between different conditions. They seek to demonstrate that these correlations differ significantly, and this analysis is often key to the studys conclusions. In this work, we assess the methods of inference which have been previously used to investigate this problem and conclude that they are inadequate. We propose a hierarchical Bayesian framework to model distant-dependent correlations in spontaneous retinal activity data and specify a method which uses the data to specify the form of the model. This model allows us to assess the evidence for/against differences in correlations between experimental conditions in a more robust and credible way. We demonstrate the use of this method by applying it to data from two studies of spontaneous retinal activity. We believe however the framework to be rather more general and that it can be used in a wide range of datasets where distance and correlation are substitute for other independent and dependent variables from experiments.

Neuroscience↗

bioRxiv2015

Bivariate spatial point patterns in the retina: a reproducible review

In this article I present a reproducible review of recent research to investigate the spatial positioning of neurons in the nervous system. In particular, I focus on the relative spatial positioning of pairs of cell types within the retina. I examine three different cases by which two types of neurons might be arranged relative to each other. (1) Cells of different type might be effectively independent of each other. (2) Cells of one type are randomly assigned one of two labels to create two related populations. (3) Interactions between cells of different type generate functional dependencies. I show briefly how spatial statistic techniques can be applied to investigate the nature of spatial interactions between two cell types. Finally, I have termed this article a reproducible review because all the data and computer code are integrated into the manuscript so that others can repeat the analysis presented here. I close the review with a discussion of this concept.

Neuroscience↗

bioRxiv2014

Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves.

Correlations in neuronal spike times are thought to be key to processing in many neural systems. Many measures have been proposed to summarise these correlations and of these the correlation index is widely used and is the standard in studies of spontaneous retinal activity. We show that this measure has two undesirable properties: it is unbounded above and confounded by firing rate. We list properties needed for a measure to fairly quantify and compare correlations and we propose a novel measure of correlation -- the Spike Time Tiling Coefficient. This coefficient, the correlation index and 33 other measures of correlation of spike times are blindly tested for the required properties on synthetic and experimental data. On the basis of this, we propose a measure (the Spike Time Tiling Coefficient) to replace the correlation index. To demonstrate the benefits of this measure, we re-analyse data from seven key studies which previously used the correlation index to investigate the nature of spontaneous activity. We re-analyse data from {beta}2(KO) and {beta}2(TG) mutants, mutants lacking connexin isoforms and also the age-dependent changes in wild type and {beta}2(KO) correlations. Re-analysis of the data using the proposed measure can significantly change the conclusions. It leads to better quantification of correlations and therefore better inference from the data. We hope that the proposed measure will have wide applications, and will help clarify the role of activity in retinotopic map formation.

Neuroscience↗