Asterics: a simple tool for the ExploRation and Integration of omiCS data.

BACKGROUND: The rapid development of omics acquisition techniques has induced the production of a large volume of heterogeneous and multi-level omics datasets, which require specific and sometimes complex analyses to obtain relevant biological information. Here, we present ASTERICS (version 2.5), a publicly available web interface for the analyses of omics datasets. RESULTS: ASTERICS is designed to make both standard and complex exploratory and integration analysis workflows easily available to biologists and to provide high quality interactive plots. Special care has been taken to provide a comprehensive documentation of the implemented analyses and to guide users toward sound analysis choices regarding some specific omics data. Data and analyses are organized in a comprehensive graphical workflow within ASTERICS workspace to facilitate the understanding of successive data editions and analyses leading to a given result. CONCLUSION: ASTERICS provides an easy to use platform for omics data exploration and integration. The modular organization of its open source code makes it easy to incorporate new workflows and analyses by external contributors. ASTERICS is available at https://asterics.miat.inrae.fr and can also be deployed using provided docker images.

Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals.

MOTIVATION: Inferring gene regulatory networks in non-independent genetically related panels is a methodological challenge. This hampers evolutionary and biological studies using heterozygote individuals such as in wild sunflower populations or cultivated hybrids. RESULTS: First, we simulated 100 datasets of gene expressions and polymorphisms, displaying the same gene expression distributions, heterozygosities and heritabilities as in our dataset including 173 genes and 353 genotypes measured in sunflower hybrids. Secondly, we performed a meta-analysis based on six inference methods [least absolute shrinkage and selection operator (Lasso), Random Forests, Bayesian Networks, Markov Random Fields, Ordinary Least Square and fast inference of networks from directed regulation (Findr)] and selected the minimal density networks for better accuracy with 64 edges connecting 79 genes and 0.35 area under precision and recall (AUPR) score on average. We identified that triangles and mutual edges are prone to errors in the inferred networks. Applied on classical datasets without heterozygotes, our strategy produced a 0.65 AUPR score for one dataset of the DREAM5 Systems Genetics Challenge. Finally, we applied our method to an experimental dataset from sunflower hybrids. We successfully inferred a network composed of 105 genes connected by 106 putative regulations with a major connected component. AVAILABILITY AND IMPLEMENTATION: Our inference methodology dedicated to genomic and transcriptomic data is available at https://forgemia.inra.fr/sunrise/inference_methods. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Defining health standards through economic optimisation: The example of colostrum management in beef and dairy production.

There is extensive literature addressing acceptable practices of colostrum distribution to new-born calves; however, no economic analyses are available concerning the profitability of this practice. Moreover, the health standards associated with colostrum management have been defined through the observation of reference farms without explicit reference to economic assessments. The objective of the current study was to evaluate the profitability of farm colostrum management and to define the optimal economic situations for given livestock systems and farm situations. The herd-level net value was calculated using the value of calf products, the cost of passive transfer failure and the cost of prevention. This value was determined for various beef and dairy scenarios and the various time periods spent managing colostrum. The maximal net values defined the optimal economic situations and enabled the determination of the optimal times for colostrum management and respective health standards (i.e., the prevalence of disorders at optimum). The results showed that the optimal time farmers should spend on colostrum management is approximately 15 min per calf. Furthermore, farmers should err on the side of spending too much time (> 15 min) on colostrum management rather than not enough, unless the cost of labour is high. This is all the more true that potential long term consequences of passive transfer failure on milk yields were not accounted for here due to scarcity of data, leading to consider this time threshold (15 min) as a minimal recommendation. This potential underestimation may arise from the greater nutrient content and bioactive compounds identified in colostrum although the passive immune transfer is here defined through immunoglobulins only. The present results show that for small farms that cannot hire colostrum managers, this work can be performed by the farmer after subcontracting other tasks. Moreover, the method proposed here-the definition of health standards through economic optimisation-is a promising approach to analysing health conventions in the cattle industry.

How Metabolic Diseases Impact the Use of Antimicrobials: A Formal Demonstration in the Field of Veterinary Medicine.

Decreasing the use of antimicrobials has become a primary objective for both human and veterinary medicine in many countries. Medical prevention and good nutrition are seen as key parameters for reducing antimicrobial use. However, little consideration has been given to how metabolic diseases may influence the use of antimicrobials in humans and animals through limiting the prevalence and severity of infectious diseases. To quantify this relationship using the example of a common metabolic disease in dairy cows (subclinical ketosis, SCK), we constructed a stochastic model reporting the total quantity of curative antimicrobials for a given population with the prevalence of cows at risk for SCK. We considered the prevalence of SCK, the relative risk of the disease in cases of SCK compared to no SCK and the use of antimicrobials to treat SCK-induced infectious diseases. Reducing the percentage of cows at risk for SCK from 80% to 10% was associated with an average decrease in the use of antimicrobials of 11% (prevalence of SCK from 34% to 17%, respectively) or 25% (prevalence of SCK from 68% to 22%, respectively), depending on the relative risk to contract SCK if risk was present. For a large percentage of the cows at risk for SCK, using a preventive bolus of monensin reduced the use of curative antimicrobials to the same level that was observed when the percentage of cows at risk for SCK was low. The present work suggests similar approaches for obesity and diabetes.