A global perspective on bioinformatics training needs, bioRxiv, 2017-02-28

AbstractIn the last decade, life-science research has become increasingly data-intensive and computational. Nevertheless, basic bioinformatics and data stewardship are still only rarely taught in life-science degree programmes, creating a widening skills gap that spans educational levels and career roles. To better understand this situation, we ran surveys to determine how the skills dearth is affecting the need for bioinformatics training worldwide. Perhaps unsurprisingly, we found that respondents wanted more short courses to help boost their expertise and confidence in data analysis and interpretation. However, it was evident that most respondents appreciated their need for training only after designing their experiments and collecting their data. This is clearly rather late in the research workflow, and suboptimal from a training perspective, as skills acquired to address a specific need at a particular time are seldom retained, engendering a cycle of low confidence in trainees. To ensure that such skill gaps do not continue to create barriers to the progress of research, we argue that universities should strive to bring their life-science curricula into the digital-data era. Meanwhile, the demand for point-of-need training in bioinformatics and data stewardship will grow. While this situation persists, international groups like GOBLET are increasing their efforts to enlarge the community of trainers and quench the global thirst for bioinformatics training.

biorxiv scientific-communication-and-education 100-200-users 2017

Multiplexed confocal and super-resolution fluorescence imaging of cytoskeletal and neuronal synapse proteins, bioRxiv, 2017-02-26

ABSTRACTNeuronal synapses contain dozens of protein species whose expression levels and localizations are key determinants of synaptic transmission and plasticity. The spectral properties of fluorophores used in conventional microscopy limit the number of measured proteins to four species within a given sample. The ability to perform high-throughput confocal or super-resolution imaging of many proteins simultaneously without limitation in target number imposed by this spectral limit would enable large-scale characterization of synaptic protein networks in situ. Here, we introduce PRISM Probe-based Imaging for Sequential Multiplexing, a method that sequentially utilizes either high affinity Locked Nucleic Acid (LNA) or low affinity DNA probes to enable diffraction-limited confocal and PAINT-based super-resolution imaging. High-affinity LNA probes offer high-throughput, confocal-based imaging compared with PAINT, which uses low affinity probes to realize localization-based super-resolution imaging. Simultaneous immunostaining of all targets is performed prior to imaging, followed by sequential LNADNA probe exchange that requires only minutes under mild wash conditions. We apply PRISM to quantify the co-expression levels and nanometer-scale organization of one dozen cytoskeletal and synaptic proteins within individual neuronal synapses. Our approach is scalable to dozens of target proteins and is compatible with high-content screening platforms commonly used to interrogate phenotypic changes associated with genetic and drug perturbations in a variety of cell types.

biorxiv bioengineering 0-100-users 2017

A practical guide for inferring reliable dominance hierarchies and estimating their uncertainty, bioRxiv, 2017-02-24

AbstractMany animal social structures are organized hierarchically, with dominant individuals monopolizing resources. Dominance hierarchies have received great attention from behavioural and evolutionary ecologists. As a result, there are many methods for inferring hierarchies from social interactions. Yet, there are no clear guidelines about how many observed dominance interactions (i.e. sampling effort) are necessary for inferring reliable dominance hierarchies, nor are there any established tools for quantifying their uncertainty. In this study, we simulated interactions (winners and losers) in scenarios of varying steepness (the probability that a dominant defeats a subordinate based on their difference in rank). Using these data, we (1) quantify how the number of interactions recorded and hierarchy steepness affect the performance of three methods, (2) propose an amendment that improves the performance of a popular method, and (3) suggest two easy procedures to measure uncertainty in the inferred hierarchy. First, we found that the ratio of interactions to individuals required to infer reliable hierarchies is surprisingly low, but depends on the hierarchy steepness and method used. We then show that David’s score and our novel randomized Elo-rating are the two best methods, whereas the original Elo-rating and the recently described ADAGIO perform less well. Finally, we propose two simple methods to estimate uncertainty at the individual and group level. These uncertainty measures further allow to differentiate non-existent, very flat and highly uncertain hierarchies from intermediate, steep and certain hierarchies. Overall, we find that the methods for inferring dominance hierarchies are relatively robust, even when the ratio of observed interactions to individuals is as low as 10 to 20. However, we suggest that implementing simple procedures for estimating uncertainty will benefit researchers, and quantifying the shape of the dominance hierarchies will provide new insights into the study organisms.Highlights<jatslist list-type=bullet><jatslist-item>David’s score and the randomized Elo-rating perform best.<jatslist-item><jatslist-item>Method performance depends on hierarchy steepness and sampling effort.<jatslist-item><jatslist-item>Generally, inferring dominance hierarchies requires relatively few observations.<jatslist-item><jatslist-item>The R package “aniDom” allows easy estimation of hierarchy uncertainty.<jatslist-item><jatslist-item>Hierarchy uncertainty provides insights into the shape of the dominance hierarchy.<jatslist-item>

biorxiv animal-behavior-and-cognition 0-100-users 2017

 

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